AI voice over generators can now turn text into speech in 24 different languages and are constantly improving due to advances in AI technology.

This allows for quick and consistent brand messaging across multiple languages, though idioms and phrases may not always translate directly, requiring experimentation for desired outcomes.

New AI voice cloning tools like ElevenLabs can create replicas of anyone’s voice from just a three-second sample and speak in various languages, allowing for scenarios such as generating speeches of public figures like Donald Trump in flawless Hindi.

ElevenLabs emphasizes the importance of using this emerging technology responsibly and not at any expense.

AI-generated content is being used in entertainment, as seen when AI created a new Drake and The Weeknd song, and in global media, such as China Media Group's AI-dubbed English documentary for international audiences.

Startups like Loora are leveraging AI to provide interactive language tutoring, offering users customized feedback on English proficiency and accent using proprietary data.

Meta AI has developed a speech translator that works for largely spoken languages, advancing AI’s role in global communication and pairing sentence data for more effective model training.

Monetizing AI-generated content is a goal for some developers, with the potential to generate income via content creation.

AI avatars and voice cloning with emotional inflection are made accessible through platforms like Vidnoz AI, which offer features such as AI video creation from text, lip-synced dubbing, subtitles, and voice cloning for a subscription fee.

AI tools like ChatGPT are widely adopted for multilingual content creation, making up a significant part of business strategy for global outreach, with 44 percent of businesses seeking to implement them.

AI is reshaping marketing, providing detailed simulations and adaptation tools, and is also transforming the way writing and creative works are produced, prompting both excitement and anxiety about implications for student learning and ethical use.

Voice cloning and AI-generated content have legitimate applications in accessibility, marketing, entertainment, and language education, but also pose risks including deepfakes, misinformation, and privacy violations if misused.

These rapidly developing tools highlight the need for clear ethical guidelines and legal frameworks to ensure responsible usage, as the pace of evolution in AI technology continues to accelerate daily.

AI can greatly accelerate the creation of educational products, with tools like ChatGPT generating course structures in minutes for review and adaptation by developers and experts.

Additional AI services such as TurboText, Webcanape, and WebX can generate titles and long-form texts, while neural networks can convert written text into realistic-sounding audio.

User feedback on AI-generated content is often collected and tabulated, and AI can also analyze feedback to summarize key positive points.

There are numerous speech recognition systems from major tech companies like Google, Meta, and Amazon, which are essential to audio-related AI services.

AI’s capability to predict words and interpret audio has enabled companies like OpenAI to develop advanced commercial projects such as DALL-E 2 and GPT-3.

Israeli-developed AI can now duplicate original actors’ voices in films for dubbing in multiple languages, with support for more languages planned.

Researchers at UCSF have developed a brain-computer interface using AI to help paralyzed patients speak through digital avatars by decoding brain signals associated with speech.

This approach uses electrodes to intercept signals intended for speech muscles and enables the computer to learn key phonemes for English word generation.

NVIDIA has made advances in natural speech synthesis, including expressive voice conversion, optimized for GPU use and available to researchers and developers.

Other AI tools, like Adobe’s Enhance Speech, use models trained on vast datasets to clean poor-quality voice recordings, efficiently removing background noise and improving clarity.

Enhance Speech is among several AI-powered noise-reduction tools that substantially improve recording quality.

While neural networks are increasingly present throughout the economy, their use demands specialized expertise, and their reliability and potential harm require careful oversight and control systems.

There are limitations to AI’s performance in truth-telling and harm prevention, as noted by experts.

OpenAI has developed a Voice Engine capable of recreating any person’s voice from text input, but it is not yet publicly available due to concerns over its misuse for deepfakes.

Developers are cautious about releasing such technologies widely, given significant risks in creating convincing fake audio for malicious purposes.

AI technology is increasingly used in education to enhance learning outcomes, improve efficiency, and provide students with real-world experiences.

AI can analyze data to determine the best methods for increasing productivity, and it can train workers in new skills and improve their performance.

AI offers better access to knowledge, reduces cost and time for learning, but also raises risks such as algorithmic bias and job redundancy due to automation.

AI algorithms inherit the biases present in their training data, reproducing them in real-world applications, and may eliminate certain human roles.

Educators and policymakers must balance AI's advantages with its risks and ensure implementation is guided by scientific and ethical standards.

Voice cloning through AI tools has become sophisticated enough that fraudsters can now use this technology for scams.

Scammers can fake calls from legitimate numbers and use AI-cloned voices to deceive people, making it hard to verify the caller's true identity.

Simple security measures like personal questions or pre-arranged "safe words" can help prevent falling victim to such scams.

Only 5–10 seconds of someone’s voice, often taken from online videos, can suffice for creating a convincing AI-generated voice duplicate.

AI-generated audio can exploit emotions and trust to manipulate victims, making such social engineering attacks more dangerous.

Voice cloning also opens up possibilities for entertainment, such as simulated political debates, and has been used in irony or parody.

Deepfake technology makes it possible to create highly realistic fake audio, video, and images, showing individuals saying or doing things they never actually did.

To convincingly clone someone's voice in a specific dialect, a large amount of original audio is needed, making the process laborious and specialized, but services exist to do so for high fees.

Advances in AI-powered GPUs have further improved the quality and efficiency of modern speech recognition and voice synthesis.

Deep voice falsification requires training an audio model on the target speaker’s recordings, after which the AI can read any text in the cloned voice.

AI text-to-speech models now require only a few minutes of a person’s voice to produce realistic imitations.

Video and audio editing tools powered by AI have become more accessible, cheap, and scalable, allowing users to create content in any language, with virtual speakers customizable for many uses.

AI achievements in language computing span from proofreading and correction software to advanced chatbots and generative programs, transforming how language is processed and used.

OpenAI has determined that it is too risky to publicly release its advanced voice cloning tool at this time.

Voice cloning technology can be used in educational settings, such as visits to schools where students interact with authentic foreign language materials, helping them connect classroom content to the real world.

Some students admit they might not learn certain language phrases without the motivation of dedicated projects like "Hello, Hong Kong!".

Teachers are encouraging students to analyze language learning scenarios and collaborate in communicating their outcomes, even emailing their assignments to relevant officials for real-world engagement.

AI platforms, leveraging machine learning and natural language processing, help educators automate tasks, analyze student progress, and offer more personalized attention on a large scale.

Chatbots for student support are making education more inclusive and fostering environments where all students can thrive.

AI’s assimilation into education is fundamentally changing how educators teach and students learn, bridging cutting-edge technologies with common classroom practices.

The adoption of low-code AI platforms means educators can build custom learning tools with minimal programming, acting as innovators and adapting quickly to new teaching methods.

Professional development and ongoing technical support are essential for teachers to confidently integrate these technologies into their teaching.

There are serious concerns regarding data privacy and security in deploying AI tools, making collaboration between educators and developers vital to put student well-being first.

Low-code AI platforms allow integration of AI into educational applications, enabling personalized, interactive learning for various environments, including classrooms and e-learning.

AI grading and new language learning systems powered by these technologies are expected to launch soon, with platforms like AppMaster providing user-friendly app creation tools for educators.

Big data support helps make teaching and learning feedback more accurate, encouraging teachers to experiment and evolve their approaches.

Generative AI is gaining momentum, raising questions about how teachers can effectively use it to enhance classroom quality.

Teachers must adapt to digital-era students’ needs by trying models like flipped classrooms and hybrid instruction, and using digital tools including AI and virtual reality to make lessons more interactive and motivating.

AI voice over generators can now turn text into speech in 24 different languages and are constantly improving due to advances in AI technology.

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Content: Home > Web3

AI Voice Over Generator: Turning Text to Speech in 24 Languages

newsonjapan.com -- Aug 15
Communication has crossed boundaries and languages in today's technology driven society.

The AI voice over generator, a sophisticated technology capable of translating written text into realistic speech in a variety of languages, is a driving force in this worldwide change. The astonishing capacity of these technologies to produce voice overs in 24 different languages, and often more, is propelling them to the forefront of digital communication. We go deep into the field of AI-driven text to voice below, giving practical tips for anybody interested in realizing its enormous potential.

Why Do Multilingual Skills Matter?

Language inclusion is critical for companies, schools, and content providers that want to reach a global audience. An AI voice over generator that handles various languages allows for a broader reach while also ensuring that no audience section feels alienated. Multilingual technologies, such as those that transform English transcripts into Mandarin audio or Spanish text into French voice, help to break down communication obstacles.

Practical User Advice:

Emphasize Quality Over Quantity: While having a tool that can translate text in several languages seems great, it is critical to emphasize output quality. Choose platforms that are well-known for their precision and realistic voice reproduction.

Adjust the Tone, pace, and Accent: A decent AI voice over generator enables users to adjust the tone, pace, and accent of the created speech. This adaptability guarantees that the discourse is genuine and connects with the intended listener.

Keep Up to Date: Because these technologies are based on AI, they are always improving. Regular software upgrades might bring new languages to the table or enhance current ones. To benefit from the most recent advances, keep your software up to date at all times.

Using Nuanced Speech to Bridge Cultural Gaps

Understanding a language entails understanding the nuances, intonations, and cultural nuances as well as the words themselves. Advanced AI voice over generators not only translate text to speech but also guarantee that the speech is emotionally appropriate. For example, the way a joke is presented in Japanese may vary from how it is shown in German. As a result, always use a tool that considers these subtleties in order to make the speech seem as genuine and culturally appropriate as feasible.

Potential Multilingual Text to Speech Applications:

E-Learning Platforms: Educators may build courses in one language and then utilize an AI voice over generator to translate them into numerous languages, guaranteeing that learners all over the globe can benefit.

Podcasts in different Languages: Podcast makers may reach a worldwide audience by giving their material in different languages without having to re-record episodes.

Global Business Presentations: Companies with a global presence may simply tailor their presentations to a variety of language audiences.

Scalability and pricing

Costs, like with any technology, might be an issue. With the rise of cloud-based solutions, however, many AI voice over producers now provide scalable price structures. There is undoubtedly a price option to meet your needs, whether you are an individual wishing to convert a few pages or an organization with mass requirements.

Data Privacy Is Important

Given that these technologies may be used to convert sensitive or private information, it is critical to address data privacy. Choose platforms that emphasize user data security to ensure that the material you convert stays private.

Extending the Multilingual Communication Landscape

As companies and organizations strive for a worldwide presence, the demand for multilingual communication has never been greater. Then there are AI voice over generators. These technologies provide companies, schools, and content producers an advantage by enabling them to cater to a varied audience.

Courses in numerous Languages: Educators and e-learning platforms may now offer their courses in numerous languages. Python programming may be learned in Mandarin by one student in Beijing and Portuguese by another in So Paulo. Learning results are improved by catering to their linguistic comfort. The student may concentrate on grasping the material rather than dealing with linguistic intricacies.

Digital Marketing: By employing the AI voice over generator to translate and vocalize their promotional material, brands can easily roll out worldwide campaigns. This not only saves time, but it also guarantees that the brand message is consistent across several languages.

IVR (Interactive Voice Response) Systems: Companies may customize their customer service lines by using AI-generated voices in several languages. This provides a more personalized client experience, which may dramatically increase user happiness and loyalty.

Podcasters, YouTube makers, and digital storytellers may utilize these technologies to make their material accessible in several languages, extending their fan base and worldwide reach.

Language and Cultural Nuances

While these AI voice over generators' skills are astounding, users should be conscious of the subtleties and complexity of various languages and cultures. Even if a technology is capable of converting text to voice in 24 languages, the user must verify that the material is culturally appropriate and respectful. Certain idioms or phrases in English, for example, may not have a direct counterpart in another language or may be misconstrued.

AI engineers are tackling these issues by training their models on culturally varied datasets in order to capture the nuances of each language. However, it is also the users' responsibility to examine and, if required, change the created information to guarantee its relevancy and appropriateness.

Best Practices for Using AI Voice Over Generators

Here are some practical advice for individuals who want to fully use the possibilities of AI voice over generators:

Always Review the Output: Before completing, always listen to the created voice over. Check that your pronunciation, intonation, and emotion are appropriate for the context of your topic.

Customize Settings: Most programs enable users to change the pace, pitch, and other characteristics of their voice. Experiment with these options to get the desired result.

Keep up to date: The disciplines of AI and machine learning are rapidly growing. Use the most recent version of the program or application, since developers are always refining and improving their algorithms.

Request input: If your material is intended for a particular linguistic group, get input from native speakers. They may reveal insights that non-natives may miss.

In conclusion

In the digital age, the AI voice over generator is changing the way we interact. Its capacity to convert text into lifelike voice in different languages bridges barriers, fosters inclusion, and makes global communication easier than ever. Remember to consider quality, cultural subtlety, and data protection as you investigate the numerous products in the text to speech domain. By doing so, you get access to more than simply a tool; you also gain access to worldwide dialogues.

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How will AI Voice help educators with building courses?

This allows for quick and consistent brand messaging across multiple languages, though idioms and phrases may not always translate directly, requiring experimentation for desired outcomes.

How will AI Voice help educators with building courses?

New AI voice cloning tools like ElevenLabs can create replicas of anyone’s voice from just a three-second sample and speak in various languages, allowing for scenarios such as generating speeches of public figures like Donald Trump in flawless Hindi.

Title:

Content: Language No Barrier: New AI tool can clone voice and make it say anything in multiple languages

Imagine former US President Donald Trump speaking in flawless Hindi. A new AI voice cloning tool by ElevenLabs can clone voices and make them say anything in a bunch of different languages. All it needs is a three-second sample clip and a bit of text as the prompt.

Mehul Reuben Das May 03, 2023 13:42:20 IST

Imagine former US President Donald Trump speaking in flawless Hindi. A new AI voice cloning tool by ElevenLabs can clone voices and make them say anything in a bunch of different languages. All it needs is a three-second sample clip and a bit of text as the prompt.

As advanced as AI-based voice cloning has been, there were a few limitations to it. For example, voice generators were mainly bound by the language of the source they were trained in or rather the language of the prompt that was given to them. Now, ElevenLabs, an American AI software developing company has come up with a tool that does away with that limitation.

ElevenLabs’ new AI tool can clone the voice of a person and make it say anything in a bunch of different languages. All it needs is a clear voice sample of about 3 seconds, although it also suggests that the longer the sample, the better will be the results. The new tool even manages to maintain the speaker’s original tone of voice.

Limitless possibilities
The creators expect that this would ‘extend the possibilities’ in a variety of industries such as publishing, gaming creation, and media. “Introducing Eleven Multilingual v1: Our New Speech Synthesis Model! We’re thrilled to launch our new model supporting seven new languages: French, German, Hindi, Italian, Polish, Portuguese, and Spanish.”

“This advancement expands the horizons for creators, game developers, and publishers, and it paves the way for using generative media to create more localized, accessible, and imaginative content,” the company said.

Following the announcement, Twitter was flooded with comments, with users testing the software on various famous faces.

To demonstrate just how capable the new voice cloning AI tool is, Eluna AI, a platform for AI-content creators experimented with a sample clip of former US President Donald Trump.

In their demo, Eluna AI showcased a small clip of Donald Trump, speaking in his native tongue, English, followed by French, Spanish, German, Hindi and Italian, almost perfectly. The generated samples even gets the accent right, almost if he was a native speaker of the new target language.

Another user changed David Attenborough’s voice to German while the BBC broadcaster discussed the prospects of AI. “With this tool, anyone can do it,” stated the Twitter user. “It’s also worth noting that fraudsters will undoubtedly exploit this one.”

ElevenLabs says that its model was designed to understand the emotion and reasoning underlying words in order to produce natural-sounding and persuasive audio. ElevenLabs has said that some numerals and symbols are currently spoken wrongly, but that it is striving to rectify this.

Who is this new tool meant to help?
The US-based company believes its technology will be valuable in a variety of areas, including education and journalism.

Game developers and publishers can build engaging, localised experiences for worldwide audiences, breaking through language barriers and connecting with players and listeners to maximise engagement and efficiency while maintaining quality and accuracy.

“Educational institutions now have the ability to develop audio content for varied users in their target languages, enhancing language comprehension and even pronunciation abilities, as well as responding to different teaching methods and learning demands,” says the report.

Because of the model’s capacity to produce unique character-like voices, audiobook and content developers may also find it beneficial.

The conundrum of AI voice genertors
Despite its benefits, ElevenLabs’ launch comes amid widespread concern about the wave of new voice cloning technology. An unidentified TikTok user went popular last month after sharing an AI-generated Drake song starring The Weeknd.

It sparked concerns about the grey area of AI-created music and whether it constitutes a copyright violation. Nonetheless, ElevenLabs claims to be ‘fully committed’ to respecting creators’ rights in the midst of technological advancements.

“At Eleven, we think that we should seek to make the best use of emerging technology, but not at any expense,” it stated.

“As we create them, we make every effort to put suitable controls in place that reduce the possibility of detrimental abuse. With this in mind, we are entirely committed to both protecting intellectual property rights and taking action against infringement.”

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Music labels are worried because of AI, thanks to a surprising new song ft. Drake X The Weeknd

Someone used AI to create a whole new song featuring Drake and The Weeknd. But because the singers never sang the song, artists and music labels are worried, how AI voice modulation and AI-generated songs can disrupt the industry.

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Artificial Imposter: 47% of Indian phone users have experienced AI voice scams, highest in the world

About half of Indian adults, or 47%, have experienced AI voice scams, nearly double the global average of 25%. Furthermore, nearly 69% of adults say they can't differentiate between a real and an AI-generated voice.

What is necessary for voice cloning to work?

ElevenLabs emphasizes the importance of using this emerging technology responsibly and not at any expense.

AI-generated content is being used in entertainment, as seen when AI created a new Drake and The Weeknd song, and in global media, such as China Media Group's AI-dubbed English documentary for international audiences.

Startups like Loora are leveraging AI to provide interactive language tutoring, offering users customized feedback on English proficiency and accent using proprietary data.

Title:

Content: Loora, an AI-driven language learning startup focused on English, has emerged from stealth to announce $9.25 million in seed funding. The company aims to improve users' conversational English skills regardless of subject matter, using voice-based interactions with its eponymous iOS assistant.

Unlike typical generative AI apps, which are mostly text-based, Loora emphasizes audio. Users interact with the app as they would with a personal human tutor. Its AI tutor can understand and help refine any user's English and accent across a wide range of topics.

Emerge led the funding round, joined by Two Lanterns Venture Partners, Kaedan Capital, and several angel investors. Tel Aviv-based Loora was founded in 2020 by CEO Roy Mor and CTO Yonti Levin. They decided to focus on English language tuition due to its global prevalence, with over 1 billion learners worldwide.

Despite the numerous existing online language learning platforms, Mor and Levin found a gap in teaching conversational English in a one-to-one environment. Traditional language learning apps – such as Duolingo, Memrise, and Babel – are great for casual learners, but inadequate for those seeking to work in English. Human tutors offer a more personalized approach, but can be expensive and inaccessible to many.

Taking advantage of recent advancements in generative AI (like those used in OpenAI's ChatGPT and the Midjourney illustrator), Loora has developed an English tutor that engages in interactive conversations, offers discussion prompts, and understands users' speech to guide their improvements. Initially, Loora created its own large language models (LLMs) in 2020, but has since transitioned to utilizing multiple third-party LLMs, each suited for different tasks. The company trains these LLMs on its own data.

Loora's main focus is on spoken English and requires users to have some prior knowledge of the language. Although the platform does not cover reading or writing, an upcoming module will introduce reading texts as conversational anchors. Therefore, if users aim to master English, they may need to supplement their learning with other sources. Regardless, Loora's approach marks an interesting advancement in the field, with potential future implications for audio interfaces in generative AI services.

Incorporating voice-based learning experiences in the language learning domain is crucial to improve pronunciation and fluency. As the no-code and low-code movement accelerates the development of tech solutions, innovative platforms like AppMaster.io can facilitate the creation of ground-breaking applications and tools for various sectors, including language learning.

The investment by Emerge, Two Lanterns Venture Partners, and Kaedan Capital is a testament to Loora's potential to revolutionize virtual English education through its domain-specific AI tutor. It will be interesting to see how this voice-driven approach shapes the future of language learning and other generative AI applications.

What is unique about Loora's AI English tutor?

Meta AI has developed a speech translator that works for largely spoken languages, advancing AI’s role in global communication and pairing sentence data for more effective model training.

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Content: Did you miss a session from MetaBeat 2022? Head over to the on-demand library for all of our featured sessions here.

Artificial speech translation is a rapidly emerging artificial intelligence (AI) technology. Initially created to aid communication among people who speak different languages, this speech-to-speech translation technology (S2ST) has found its way into several domains.  For example, global tech conglomerates are now using S2ST for directly translating shared documents and audio conversations in the metaverse.

At Cloud Next ’22 last week, Google announced its own speech-to-speech AI translation model, “Translation Hub,” using cloud translation APIs and AutoML translation. Now, Meta isn’t far behind.

Meta AI today announced the launch of the universal speech translator (UST) project, which aims to create AI systems that enable real-time speech-to-speech translation across all languages, even those that are spoken but not commonly written.

“Meta AI built the first speech translator that works for languages that are primarily spoken rather than written. We’re open-sourcing this so people can use it for more languages,” said Mark Zuckerberg, cofounder and CEO of Meta.

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According to Meta, the model is the first AI-powered speech translation system for the unwritten language Hokkien, a Chinese language spoken in southeastern China and Taiwan and by many in the Chinese diaspora around the world. The system allows Hokkien speakers to hold conversations with English speakers, a significant step toward breaking down the global language barrier and bringing people together wherever they are located — even in the metaverse.

This is a difficult task since, unlike Mandarin, English, and Spanish, which are both written and oral, Hokkien is predominantly verbal.

How AI can tackle speech-to-speech translation

Meta says that today’s AI translation models are focused on widely-spoken written languages, and that more than 40% of primarily oral languages are not covered by such translation technologies. The UST project builds upon the progress Zuckerberg shared during the company’s AI Inside the Lab event held back in February, about Meta AI’s universal speech-to-speech translation research for languages that are uncommon online. That event focused on using such immersive AI technologies for building the metaverse.

To build UST, Meta AI focused on overcoming three critical translation system challenges. It addressed data scarcity by acquiring more training data in more languages and finding new ways to leverage the data already available. It addressed the modeling challenges that arise as models grow to serve many more languages. And it sought new ways to evaluate and improve on its results.

Meta AI’s research team worked on Hokkien as a case study for an end-to-end solution, from training data collection and modeling choices to benchmarking datasets. The team focused on creating human-annotated data, automatically mining data from large unlabeled speech datasets, and adopting pseudo-labeling to produce weakly supervised data.

“Our team first translated English or Hokkien speech to Mandarin text, and then translated it to Hokkien or English,” said Juan Pino, researcher at Meta. “They then added the paired sentences to the data used to train the AI model.”

For the modeling, Meta AI applied recent advances in using self-supervised discrete representations as targets for prediction in speech-to-speech translation, and demonstrated the effectiveness of leveraging additional text supervision from Mandarin, a language similar to Hokkien, in model training. Meta AI says it will also release a speech-to-speech translation benchmark set to facilitate future research in this field.

William Falcon, AI researcher and CEO/cofounder of Lightning AI, said that artificial speech translation could play a significant role in the metaverse as it helps stimulate interactions and content creation.

“For interactions, it will enable people from around the world to communicate with each other more fluidly, making the social graph more interconnected. In addition, using artificial speech translation for content allows you to easily localize content for consumption in multiple languages,” Falcon told VentureBeat.

Falcon believes that a confluence of factors, such as the pandemic having massively increased the amount of remote work, as well as reliance on remote working tools, have led to growth in this area. These tools can benefit significantly from speech translation capabilities.

“Soon, we can look forward to hosting podcasts, Reddit AMA, or Clubhouse-like experiences within the metaverse. Enabling those to be multicast in multiple languages expands the potential audience on a massive scale,” he said.

How Meta’s universal speech translator (UST) works

The model uses S2UT to convert input speech to a sequence of acoustic units directly in the path, an implementation Meta previously pioneered. The generated output consists of waveforms from the input units. In addition, Meta AI adopted UnitY for a two-pass decoding mechanism where the first-pass decoder generates text in a related language (Mandarin), and the second-pass decoder creates units.

To enable automatic evaluation for Hokkien, Meta AI developed a system that transcribes Hokkien speech into a standardized phonetic notation called “Tâi-lô.” This allowed the data science team to compute BLEU scores (a standard machine translation metric) at the syllable level and quickly compare the translation quality of different approaches.

In addition to developing a method for evaluating Hokkien-English speech translations, the team created the first Hokkien-English bidirectional speech-to-speech translation benchmark dataset, based on a Hokkien speech corpus called Taiwanese Across Taiwan.

Meta AI claims that the techniques it pioneered with Hokkien can be extended to many other unwritten languages — and eventually work in real time. For this purpose, Meta is releasing the Speech Matrix, a large corpus of speech-to-speech translations mined with Meta’s innovative data mining technique called LASER. This will enable other research teams to create their own S2ST systems.

LASER converts sentences of various languages into a single multimodal and multilingual representation. The model uses a large-scale multilingual similarity search to identify similar sentences in the semantic space, i.e., ones that are likely to have the same meaning in different languages.

The mined data from the Speech Matrix provides 418,000-hour parallel speech to train the translation model, covering 272 language directions. So far, more than 8,000 hours of Hokkien speech have been mined together with the corresponding English translations.

A future of opportunities and challenges in speech translation

Meta AI’s current focus is developing a speech-to-speech translation system that does not rely on generating an intermediate textual representation during inference. This approach has been demonstrated to be faster than a traditional cascaded system that combines separate speech recognition, machine translation and speech synthesis models.

Yashar Behzadi, CEO and founder of Synthesis AI, believes that technology needs to enable more immersive and natural experiences if the metaverse is to succeed.

He said that one of the current challenges for UST models is the computationally expensive training that’s needed because of the breadth, complexity and nuance of languages.

“To train robust AI models requires vast amounts of representative data. A significant bottleneck to building these AI models in the near future will be the privacy-compliant collection, curation and labeling of training data,” he said. “The inability to capture sufficiently diverse data may lead to bias, differentially impacting groups of people. Emerging synthetic voice and NLP technologies may play an important role in enabling more capable models.”

According to Meta, with improved efficiency and simpler architectures, direct speech-to-speech could unlock near-human-quality real-time translation for future devices like AR glasses. In addition, the company’s recent advances in unsupervised speech recognition (wav2vec-U) and unsupervised machine translation (mBART) will aid the future work of translating more spoken languages within the metaverse.

With such progress in unsupervised learning, Meta aims to break down language barriers both in the real world and in the metaverse for all languages, whether written or unwritten.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.

Monetizing AI-generated content is a goal for some developers, with the potential to generate income via content creation.

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Content: Harnessing the power of AI in your marketing plan doesn’t mean you’re abdicating control, writes Chris Pollinger. Instead, it means you’re arming yourself with a powerful ally that can help you navigate the complex world of real estate marketing with more clarity, precision, and insight.

In the bustling world of real estate marketing, there’s a transformative player that’s been making quite a buzz lately — artificial intelligence (AI). According to Forbes Advisor, 97 percent of business owners believe that AI, specifically ChatGPT, will positively impact their businesses. This comes as no surprise given AI’s projected contribution of a 21 percent net increase to the United States GDP by 2030.

ChatGPT, in particular, has been winning hearts and minds in the business community, with 1 million users hopping onboard within the first five days of its release. These remarkable figures indicate the enormous potential of AI to revolutionize your real estate marketing strategies.

However, using AI merely for content creation is just the tip of the iceberg. It’s time to dig a little deeper and uncover how AI can truly elevate your real estate business.

1. Tailoring content with a unique voice

Every piece of content you create as a marketer speaks to your audience. AI can help you make that connection even more personal by enabling you to create content in your unique voice or that of your company. This world is evolving not year by year, or even month by month, but day by day. We are wicked close to hyper-personalized marketing, where AI can reach each person you market to and craft messages to them specifically, all while doing so in your voice and on-brand.

With the right prompts, AI can not only write in various tones — casual, technical, serious, playful, you name it — but also replicate a specific content creator’s style. This capability could explain why one in three businesses plan to use ChatGPT for creating website content, according to a Forbes Advisor survey.

2. Breaking language barriers

In a globalized world, the ability to communicate in multiple languages is vital. ChatGPT can translate your content into dozens of languages, providing an invaluable tool for reaching a diverse audience. This capability is so coveted that 44 percent of businesses aim to use ChatGPT for multilingual content creation.

While generative AI tools aren’t dedicated translators, their user-friendly interfaces and rapid response times make them suitable for simple translations.

3. Exploring marketing scenarios

One of the fascinating applications of AI lies in its ability to simulate a multitude of marketing scenarios, facilitate unique role-playing exercises, and generate adaptive responses to various challenges. This means you have a virtual ‘sandbox’ at your disposal, where you can explore, experiment, and learn without any real-world repercussions.

By carefully defining your objective, setting the context, specifying roles, and crafting a storyline, you can guide AI to generate insightful responses and action plans. This could involve mimicking potential customer interactions, simulating responses to different marketing campaigns, or envisioning how various scenarios might play out based on existing data.

You could be wondering how your customers might react to a new product launch or how a certain demographic might perceive a new marketing campaign. With AI, these simulations can become a part of your planning and strategy process.

These simulations are not just about creating hypothetical situations. They can help you anticipate potential pitfalls, devise strategies to overcome them and identify opportunities that you might have overlooked otherwise. For instance, AI could simulate customer reactions to a new pricing strategy or a new product feature, helping you fine-tune your approach based on the feedback generated.

Of course, leveraging AI for such advanced use-cases involves more than just inputting a basic command. It requires clear and thoughtful prompts along with an understanding of your business context. However, the insights you can gain from these simulations are worth the extra effort. They can provide you with a comprehensive understanding of the potential outcomes of your marketing strategies, helping you make informed decisions and avoid costly mistakes.

Ultimately, the goal is to make your AI tool a strategic partner, one that helps you analyze, plan, and predict outcomes more accurately. This is not about replacing human creativity or intuition; it’s about augmenting it with powerful, data-driven insights. When used correctly, AI can become an invaluable tool in your marketing arsenal, helping you navigate complex marketing landscapes with greater confidence and foresight.

This is a paradigm shift in how we understand and approach marketing strategy development. By embracing AI, we’re not just streamlining processes or increasing efficiency; we’re redefining the very framework of strategic marketing planning. Let’s welcome this change and see how far it can take us.

4. Inspiring brainstorming sessions

Who says AI can’t be creative? When inspiration is hard to come by, AI can be a surprising ally for brainstorming fresh marketing ideas. Especially when you get in the habit of asking it about things you aren’t thinking about.

When we were training our team of AI Advisors, we started with on the world of luxury real estate and the accompanying client expectations. We also included the needs of our clients, the real estate business owner. The AI Advisors each have areas of specialty, are trained to exceed expectations, to deliver not only the answer to the user’s question but to also deliver the phycology and reasoning behind it.

Consider AI as a conversation starter, a brainstorming partner that can suggest novel marketing ideas based on your brand’s identity and customer demographics. You can even integrate AI into your team brainstorming sessions for additional input or refining ideas. Let your creativity fly.

5. Crafting your marketing plan

Crafting a comprehensive marketing plan is no small feat. It’s like putting together an intricate jigsaw puzzle with numerous moving parts. But here’s the good news — AI can be a valuable co-pilot on this journey. By breaking the process down into manageable steps and incorporating AI into each phase, you can create a marketing plan that aligns with your business goals and boosts your overall productivity.

Considering that 64 percent of businesses expect AI to increase productivity, this AI-assisted approach holds immense promise.

Let’s delve into some key aspects of the marketing plan where AI can lend its genius:

  1. Defining marketing objectives: To start off, we need to identify what we want to achieve. AI can analyze your past performance, identify patterns and trends, and then suggest realistic and actionable objectives for your business.
  2. Identifying target audiences: Knowing your audience is pivotal to your marketing success. AI can help you analyze customer data and behavior patterns, segmenting your audience and identifying your key demographics more accurately.
  3. Formulating a content plan: A well-structured content plan is the backbone of your marketing strategy. With AI, you can predict trending topics, assess content performance, and tailor content to your audience’s preferences.
  4. Designing specific campaigns: AI can boost the effectiveness of your campaigns by suggesting personalized communication strategies, optimizing campaign timings, and recommending the most impactful channels to reach your audience.
  5. Allocating budgets: Budget allocation is a critical aspect that needs careful consideration. AI can analyze historical data, assess the ROI of different channels, and suggest a budget allocation strategy that maximizes your return on investment.
  6. Setting KPIs and success metrics: What gets measured gets managed. AI can help identify key performance indicators and success metrics that align with your business goals, providing a clear roadmap to success.
  7. Creating an implementation plan: AI can streamline the execution of your marketing plan by automating tasks, scheduling posts, and providing actionable insights to optimize performance in real time.
  8. Analyzing results and optimizing: AI is excellent at crunching numbers. It can evaluate campaign performance, provide real-time analytics, and suggest tweaks for improving future campaigns.

By integrating AI into these areas, you can build an effective marketing plan that not only aligns with your business goals but also adapts to changing market dynamics.

Harnessing the power of AI in your marketing plan doesn’t mean you’re abdicating control. Instead, it means you’re arming yourself with a powerful ally that can help you navigate the complex world of real estate marketing with more clarity, precision, and insight. The future of marketing is here, and it’s intelligent, agile, and data-driven. Are you ready to seize it?

Chris Pollinger, founder and managing partner of RE Luxe Leaders, is the profit whisperer to the leadership elite in the business of luxury real estate. He is a national speaker, consultant and leadership coach. Learn more about his broker, manager and team leader growth programs at RELuxeLeaders.com

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AI avatars and voice cloning with emotional inflection are made accessible through platforms like Vidnoz AI, which offer features such as AI video creation from text, lip-synced dubbing, subtitles, and voice cloning for a subscription fee.

AI tools like ChatGPT are widely adopted for multilingual content creation, making up a significant part of business strategy for global outreach, with 44 percent of businesses seeking to implement them.

AI is reshaping marketing, providing detailed simulations and adaptation tools, and is also transforming the way writing and creative works are produced, prompting both excitement and anxiety about implications for student learning and ethical use.

Title:

Content:
This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:

fact-checked

trusted source

proofread

How is AI changing the way we write and create?

Since late last year, artificial intelligence platforms like ChatGPT have become a growing topic of conversation on college campuses, with students using the technology for everything from class assignments to essays.

These text-generating software programs sift through massive databases to generate human-like responses to prompts or questions from users. The rapid introduction of this technology and its relatively unknown potential have spawned both awe and apprehension.

So what are the possible positive and negative effects of these tools? How might they change how we think about writing, creativity, authenticity and teaching? What is the path forward?

To better understand these questions, we spoke with three scholars in NC State's Department of English. Our faculty offer insights on the technology's societal and ethical ramifications, how to deal with issues like plagiarism, and the importance of increasing AI literacy, among other topics.

What are the cognitive consequences of machine-generated writing?

Chris Anson, Professor of English: Written communication represents myriad purposes and genres across thousands of different contexts. Much of it is created to handle routine tasks, such as describing a home for a real estate listing, sending an apology letter to a customer or providing accurate directions to a location.

In such cases, using AI-based natural language processors (NLP) to fulfill the task does little to challenge the cognitive processes of the human writer. The reason is that the writer is ordinarily not significantly changed by the writing task, especially when it uses boilerplate-like language—language that is often repeated with a few unique details inserted. Instead, these software improve efficiency and make time for the person to do higher-level, more cognitively sophisticated kinds of writing.

However, when people compose unique texts that require complex reasoning—the framing and support of arguments, and choices of structure, language and style—their composing process alternates between mental formulation and textual output. Writers test and evaluate their visual representation of thought on a page or screen as it emerges, discovering new ideas and subsequently revising the text. Writing can change the writer, opening up new perspectives and beliefs or revealing what there still is to learn.

Especially in , the reciprocity of writing and thinking is essential for intellectual development and higher-order reasoning. Asking an AI-based system to write an essay on a topic that the (human) writer has not yet explored significantly subverts the thinking and learning process.

It is possible for a writer to auto-generate a text, evaluate whether it reflects the writer's thoughts or intentions, and then revise the text as needed. But this process doesn't work for many genres such as explanations of scientific processes or historical accounts because the writer is relying on the machine to provide information they don't yet know.

Representing new knowledge in writing solidifies the knowledge through its (re)articulation, leading to stronger learning. In this sense, when used to replace human composing entirely, AI-based NLP systems threaten the integrity of our educational system and the future intellectual acumen of our students.

Because NLP systems increasingly will become part of our daily lives, educators need to find principled ways to integrate them into instruction. For example, I asked ChatGPT to explain the cognitive consequences of machine-generated writing, it gave me an additional idea that I had not considered, but only after I had written my statement. The software's response? "Machine-generated writing may lead to a homogenization of writing style…"

As ChatGPT itself recommends, "it is important for people to remain aware of these potential effects and to use machine-generated writing in conjunction with, rather than as a replacement for, human-generated writing."

What are some ethical considerations of machine-generated content?

Huiling Ding, Professor of English: AI-generated content, be it texts or artwork, introduces many ethical challenges related to authorship, copyright, creativity, plagiarism and labor practices. For instance, text-to-image AI generators like Midjourney and DALL-E 2 use images available in the and/or images available online through Google search, Pinterest, and other image-sharing and art-shopping platforms as training data for their algorithms.

By supporting text-prompt-driven image creation, these AI generators then produce artwork that can imitate individual artists' styles. In doing so, they compete with if not displace artists who have spent decades improving their craft.

AI-assisted writing faces similar challenges in terms of transparency, explainability, plagiarism and authorship attribution. Using online texts as training data, AI writers such as GPT-3 can generate original summaries and syntheses based on existing content.

Traditional writing classes are disrupted by these AI tools, which speed up and automate the process of online research and the summary and synthesis of reference materials. Students can easily copy and paste AI-generated content as their own written work without being caught by plagiarism-detecting tools such as Turnitin.

In other words, natural language generation tools such as GPT-3 transform how we detect and define plagiarism. That, in turn, calls for new research and adaptation from writing instructors and scholars.

Outside the classroom, professional writers and businesses use AI content generators to create preliminary ideas, generate quick summaries of online publications, write stories and engage with customers in chatbot conversations.

While famous artists such as Greg Rutkowski may feel their rights infringed by AI art generators, other artists are using AI-generated art for inspiration. In the content generation marketplace, these AI tools can compete with writers and artists or can be used as human-augmenting tools to help writers and artists produce content more creatively, efficiently and collaboratively.

How do advancements in AI technologies affect how we teach writing?

Paul Fyfe, Associate Professor of English: At the start of this year, ChatGPT made many people nervous about the potential impact of AI on student writing. Even though generative AI will likely affect various professions and domains, student writing became a lightning rod for concerns about cheating, as if students could press a button and produce essays or completed homework. However, the commentary hasn't necessarily reflected students' experiences; the reality is more complicated.

For the past few semesters, I've given students assignments to "cheat" on their final papers with text-generating software. In doing so, the majority of students learn (often to their surprise) as much about the limits of these technologies as their seemingly revolutionary potential. Some come away quite critical of AI, believing more firmly in their own voices. Others become curious about how to adapt these tools for different goals, or what professional or educational domains they could impact. Few, however, believe they can or should push a button to write an essay; none appreciate the assumption they will cheat.

Grappling with the complexities of "cheating" also moves students beyond a focus on specific tools, which are changing stunningly fast, and toward a more generalized AI literacy. Frameworks for AI literacy are still being developed; mechanisms for teaching it are needed just as urgently.

Beyond ChatGPT, faculty and administrators must reckon with where AI literacy fits into their , at levels from K-12 through higher ed. Experimenting with AI in the classroom can help faculty members learn alongside students what kinds of assignments and learning opportunities these tools might open, what critical perspectives should support them, and what guardrails we still need.

Yet not every class can or should focus on these technologies, even if they're likely to be affected by them. While it's difficult to coordinate an institutional response to fast-moving technologies, generative AI seems significant enough to warrant such collective action. As AI becomes more common, so might an engaged, interdisciplinary AI literacy become a common aspect of students' educations.

Citation: How is AI changing the way we write and create? (2023, March 28) retrieved 28 March 2023 from https://phys.org/news/2023-03-ai-1.html
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How ChatGPT robs students of motivation to write and think for themselves

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Voice cloning and AI-generated content have legitimate applications in accessibility, marketing, entertainment, and language education, but also pose risks including deepfakes, misinformation, and privacy violations if misused.

What are some risks regarding AI voice clning?

These rapidly developing tools highlight the need for clear ethical guidelines and legal frameworks to ensure responsible usage, as the pace of evolution in AI technology continues to accelerate daily.

AI can greatly accelerate the creation of educational products, with tools like ChatGPT generating course structures in minutes for review and adaptation by developers and experts.

Title:

Content: Columns
How to use AI when creating educational courses?
Columns
Tatyana Galkina
Director of iSpring Academy
Alina Aleshchenko
In various industry communities, there is an active discussion about whether AI and machine learning technologies should be applied in the field of education.
It is believed that soon neural networks will completely replace the developers of courses and other educational products.
But that's not true.
AI is a tool that helps and works only in experienced hands, without a “guide ” it is of little use.
How technologies will affect the quality of training, how they are used today by developers of EdTech solutions and what are the obstacles for the widespread introduction of AI in education, says Tatyana Galkina, director of the iSpring Academy.
How to use AI when creating educational courses?
Make artificial intelligence self-learn and improve – choose online courses in the catalog of courses on machine learning.
There are two important points that neural networks will help improve in the learning process.
• First, neural networks will save the sphere from excessive conservatism and clumsiness – AI becomes a good incentive for the study and use of new technologies.
Second, AI can accelerate the process of creating educational products for too long.
Often, courses become obsolete even in the development process, so speed is of great importance.
Reducing the time of content preparation will make training more relevant and timely.
We expect that in the near future, neural networks will allow corporate universities, online schools and universities to accelerate the development of courses - they will take over the function of packaging content.
Now they can be assigned part of the preparatory tasks.
Task number one – generation of images and texts
Developing courses, we use AI to search for interesting ideas, packaging content, generating selling, engaging titles for the course, images.
Experts, experienced designers, methodologists work with neural networks.
Usually it is quite difficult to find a finished image on the stocks that meets all the requests.
For example, a developer is looking for an illustration for the cover of a course about leadership competencies.
He needs the image of a strong, strong-willed pilot at the helm of the aircraft.
AI can offer its own options or adjust the finished picture: change the angle, colors, some details, and thus generate a unique illustration that can be further used in the work.
The main thing is not to forget that artificial intelligence is still not an expert, and the reliability of the content it creates always needs to be checked.
After all, the neural network, as an artist, can depict anything, even the jungle on Mars, in its own way interpret the elements of the clothes of the same aircraft pilot, draw non-existent in reality details.
Therefore, when developing training courses with the help of neural networks, you need to be extremely careful.
With images work:
Artificial intelligence is able to help with the generation of ideas, topics, structures, metaphors of the course, can write a dialogue between the manager and the client or come up with a test question with answers.
You can compare this with brainstorming an entire team, only it will take several times less time and effort.
But in this case, the work of the expert should be even more painstaking and thoughtful than with images.
Neural networks cannot be trusted implicitly — they may well come up with non-existent facts.
Read on topic:
Five neural networks that will color your photos
Will come up with a name for the brand and pitch the project to the investor: a selection of neural networks for copywriters
For example, we needed to create a course for retail employees about merchandising rules.
For the developer, this topic was new.
Going the standard way, he would have spent hours, if not days, to find sources of information, dive in, delve into and structure the course, or take the expert ’ s time to find out what needs to be included in the course.
AI helped to generate the structure in 5 minutes, it took another 15 minutes to check its adequacy and adjust it to the task of the course and send it to the expert for approval.
Further, for each item of the structure, the developer selected materials, including with the help of colleagues.
In this part of the work on the course, we no longer rely on AI.
In addition to ChatGPT, the generation of texts can be assigned to:
• CopyMonkey (analogues: ruGPT-3, Smodin) — 10 text formats are available.
• TurboText (analogues: Webcanape, WebX) — will come up with a title for a longread, course or text.
Task number two – work with sound and video
Virtual assistants help create unusual video effects to engage in the learning process.
In addition, there are tools for creating talking characters.
Neural networks are able to improve the quality and resolution of videos, process audio tracks and generate unique background music suitable for the course.
One of the frequent cases of using a neural network in training courses is voice acting by a robot.
No need to waste time searching for a speaker, recording in the studio.
You can just write a text, and the neural network will voice it.
It makes it a natural voice.
AI quite well understands the Russian text, accents, nuances of pronunciation.
Our course designer already has such functionality, and we actively use it ourselves.
In this segment will be useful:
• Gen-2 — changes the background of the video, removes unnecessary objects from the picture, adds the desired stylization.
• Synthesia Create — turns a script into a video course.
• iSpring Suite Max (analogues: Freetts, Text to Speech Online, VoxWorker) - one of the constructor tools turns text into voiceover for an online course or video.
• Boomy (analogue – MuseNet) – will generate a melody on request.
In addition, neural networks are used for:
• search for new ideas for the promotion of educational products;
• optimization and automation of the learning process;
• processing and ranking of reviews;
• writing macros to translate PDF files into pictures;
• development of standard TK.
For example, a developer sends a feedback questionnaire to Google Forms to those who have completed an online course in order to receive feedback.
Respondents write what they liked or did not like, the results are collected in the table.
How to process them?
You can unload all ready-made detailed answers and ask the neural network to rank them from the most negative to the most positive.
Or analyze and write down the 5 most positive points.
Task number three — specification of issues and language practice
In addition to generating and processing content, AI as an assistant can clarify user training questions and direct them to experts.
Such mechanics can now be traced in various chatbots - according to standard algorithms, they help to correctly formulate requests.
This also applies to training.
The second scenario is independent language practice.
With the same ChatGPT you can talk in any foreign language – check yourself after the lessons of the expert, consolidate the acquired knowledge.
To talk with the help of chatbots to learn is unrealistic, but they allow you to practice.
See also: Creating a website with the help of neural networks - from the logo to the final layout
What to entrust to AI is definitely not worth it
Especially carefully you need to approach the automation of assessments and verification of homework.
Artificial intelligence can invent any answer and then rely on it.
Therefore, the system of control over it should be very clearly thought out.
It is also better to form the educational trajectory and individual training programs personally, because the neural network does not take responsibility for the result of training.
It is not recommended to trust the AI to compile lists of literature, as they may appear non-existent books, sites and other sources.
It is also not necessary to instruct the neural network to write a script for working with some unique equipment or software, since it can take information not only from available documentation, but also come up with it.
Difficulties in implementation
The mass introduction of neural networks in educational processes is hampered by a number of serious factors:
• lack of control and verification of the created content;
• the risk of leakage of personal data and information constituting a trade secret.
In addition, the use of AI in education is expected to generate a large number of untested courses.
In the pursuit of profit, they will generate everything in a row, but only serious providers and large sites will monitor the reliability.
And this can have a negative impact on the quality of the training itself.
Market participants need a thoughtful and conscious approach, an understanding of what tasks need to be solved with the help of AI and content verification with an expert.
And consumers need to check vendors and choose reliable sites that are ready to be responsible for the created content.
Feedback from curators, experts, teachers, organization of the process is important.
The finished course is still only one part of the educational experience that the user receives during the course of training.
EdTech is more likely to use AI correctly than other areas, as developers understand the value of learning and have a lot of experience in correctly presenting and verifying information.
Therefore, neural networks for them will become an assistant and a friend, not an enemy and a competitor.
Photo credit: Shutterstock / Stock-Asso
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Additional AI services such as TurboText, Webcanape, and WebX can generate titles and long-form texts, while neural networks can convert written text into realistic-sounding audio.

User feedback on AI-generated content is often collected and tabulated, and AI can also analyze feedback to summarize key positive points.

There are numerous speech recognition systems from major tech companies like Google, Meta, and Amazon, which are essential to audio-related AI services.

Title:

Content: OpenAI, a non-profit artificial intelligence developer, claims that its speech recognition software is highly efficient.
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The non-profit organization OpenAI, whose goal is to develop and implement artificial intelligence (AI) for the benefit of all mankind, released the Whisper system in open access (release).
Whisper is an automatic speech recognition technology that, according to OpenAI, allows for “reliable ” transcription in multiple languages.
In addition, Whisper automatically translates speech from different languages into English.
advertising
Speech transcription occurs automatically.
Voice Record
Automatic speech recognition (ASR) has always challenged artificial intelligence and machine learning.
Thanks to the Whisper program, OpenAI has taken another successful step in the development of this direction.
A lot of different options
There are a huge number of different speech recognition systems that are the basis of the software and services of such technology giants as Google, Meta and Amazon.
A distinctive feature of Whisper is that this platform has been trained for 680,000 hours based on data collected from the Internet in multilingual and multitasking mode.
This approach has improved the recognition of unique accents, background noise variations, as well as technical terminology and jargon.
"The main intended users of Whisper models are AI specialists who study the reliability, potential, errors, generalization and limitations of the current model.
However, Whisper can also be potentially useful as a solution for automatic speech recognition among developers, especially for English speech recognition. "said OpenAI representatives in the GitHub repository.
Anyone can download Whisper from GitHub; it ’ s completely free.
Models have demonstrated their capabilities
In a press release, OpenAI said: "The models performed well in ASR in about 10 languages.
Tailored to perform certain tasks, such as detecting voice activity, dictaphone recording, and classifying speakers, they can demonstrate a host of useful benefits.
However, they have not yet been thoroughly tested in these areas. ”
Limitations of technology
In certain areas, such as text forecasting, Whisper has certain disadvantages.
Since the system was trained on a large number of "noisy" data sets, the company warns that Whisper may include in its transcriptions words that were not actually spoken.
This may be due to the need to predict the next word and at the same time try to decipher the audio stream.
In addition, Whisper does not work equally well in different languages.
When working with native speakers of languages that are underrepresented in training data or models, the system allows a higher percentage of errors.
The company says: “Although Whisper models cannot be used for real-time transcription out of the box, their speed and versatility allow specialists to develop products based on them that can recognize and translate speech almost instantly.
The true value of applications built on Whisper models suggests that the disparate performance of these systems can have real economic benefits. "
OpenAI is not limited to Whisper technology.
Currently, the company is also engaged in the creation of commercial projects such as DALL-E 2 and GPT-3.
In addition, OpenAI constantly conducts purely theoretical developments, one of which is artificial intelligence systems, which are trained by studying recorded video materials.
Source: GitHub Repository
1. (https: / / github.com / openai / Video-Pre-Training)
2. (https: / / github.com / openai / whisper / blob / main / model-card.md)
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AI’s capability to predict words and interpret audio has enabled companies like OpenAI to develop advanced commercial projects such as DALL-E 2 and GPT-3.

Israeli-developed AI can now duplicate original actors’ voices in films for dubbing in multiple languages, with support for more languages planned.

Title:

Content: Artificial intelligence developed by the Israelis is able to duplicate films with the voices of the original
Israeli startup Deepdub has developed a service for translating video content into new languages using machine learning algorithms.
The company uses neural networks to generate the speech of original actors from movies, TV shows, games and advertising.
AI processes voices and then translates them into a new language, preserving the timbre, rhythm, intonation and other important voice nuances in the work of a professional artist.
Deepdub promises to solve the main problems of industries related to voiceover and duplication.
According to Aberdeen, an average of five minutes of storytelling takes an hour to work in a recording studio.
And if the dubbing actor wants to match the original track as much as possible, the time spent on dubbing can increase by another two times.
At the same time, the cost of such services is a significant part of the budget for filmmakers and video game developers - a minute of duplication of one person per language on average costs about $75 for a simple video.
The startup aims to create a one-stop solution for content makers who want to go international or reduce their own costs for translators.
Using synthetic voices based on the original voice patterns of the actors, the startup duplicates movies, games and advertising in the post-production phase.
According to the developers, in addition to reducing costs, dubbing with the help of neural networks gives another advantage - AI reproduces the voice of the original, so the viewer will always watch the film in the form in which it was conceived by the director and performed by the actor. "Our artificial intelligence models allow you to reproduce the characteristics of the voice, using no more than three minutes of original voice data.
The AI-generated voice in the target language can be reproduced at any level of expressiveness, including crying, screaming, talking with food in the mouth, and more — even if the original voice data did not contain this information, ” said Deepdub co-founder Nir Krakowski.
Additionally, Deepdub ’ s algorithms track facial expressions and lip movements of actors.
Thus, the output of the audio track of the startup fully corresponds to how the voice actors work.
The current version of the platform supports six languages, and the startup plans to add six more before the end of next year.
In the long term, the company also intends to take its algorithms to the next level – to teach AI to duplicate voices in real time.
Among the famous works of Deepdub Krasowski mentioned the English-language thriller “Every time I die ” 2019.
The startup dubbed the film into Spanish and Portuguese.
According to the developers, this is one of the first cases when a full-fledged film with synthesized voices was released in the world.
Recently, Deepdub raised $20 million in the series A round. The company will direct the funds received to improve its technologies.

Eleven Labs is extending its voice cloning services for which industries?

What company has developed a service to translate original video content into multiple languages using machine learning algorithms?

Researchers at UCSF have developed a brain-computer interface using AI to help paralyzed patients speak through digital avatars by decoding brain signals associated with speech.

Title:

Content: Researchers at the University of California, San Francisco (UCSF) have developed a special brain-computer interface with support for artificial intelligence (AI) that allowed a woman with severe paralysis as a result of a brain stem stroke to speak through her digital “avatar. ”
This is reported by the portal Medical Xpress.
The translation of the main provisions of the publication is presented by discover24.ru.
Edward Chang, MD, chair of the Department of Neurological Surgery at the University of California, San Francisco, has been working on a technology known as a brain-computer interface (BCI) for more than a decade.
“The goal of our research project is to help patients who have lost their speech restore the full way of communication that is most natural for people.
New achievements bring us closer to making it real, ” he said.
Earlier, Chang ’ s research team showed the possibility of decoding brain signals into text in a person who had a brain stem stroke many years ago.
The latest study demonstrates something more ambitious: decoding brain signals into natural speech and facial expressions that animate a person ’ s face during a conversation.
Chang implanted a paper-thin rectangular mini-board consisting of 253 electrodes on the surface of the brain in areas that are critical for speech functions.
The electrodes intercepted the patient ’ s brain signals, which, if not for a previous stroke, would have reached her tongue, jaw and larynx muscles, as well as facial muscles that form facial expressions.
A cable connected to a port attached to the patient ’ s head from the outside connected the electrodes to the computer unit.
For several weeks, the participant of the experiment worked with researchers on training AI algorithms for the recognition system of unique signals of her brain, providing speech functions.
This involved repeatedly repeating various phrases from a conversational set of 1024 words until the AI achieved confident recognition of patterns of brain activity associated with sounds.
Instead of teaching the AI to recognize whole words, the researchers created a system that decodes words from phonemes — stable subunits of speech that form spoken words in the same way that letters form written words.
Using this approach, the computer had to learn just 39 phonemes to decipher any word in English.
This simultaneously increased the accuracy of the system and made it three times faster.
Next, to mimic the voice, the researchers developed a speech synthesis algorithm that they personalized so that it sounded like the patient ’ s voice before the injury, using her archived video recordings.
Chang ’ s research team eventually animated the avatar with software that mimics and animates facial muscle movements developed by Speech Graphics based on AI technology.
The researchers created tailor-made machine learning processes that allowed the standard software to process signals sent from a woman ’ s brain as she tried to speak and adequately translate them into facial expressions on the avatar ’ s face, including reflections of facial movements in happiness, sadness, and surprise.
"Essentially, we are making up for the connections between the brain and the vocal tract that have been severed by a stroke.
When the patient first used this system to speak and move the face of the avatar at the same time, it was expected to have a real effect, ” said researchers working with Professor Chang, PhD student Kylo Littlejohn, and Dr. Gopala Anumanchipalli, a professor of electrical engineering and computer science at the University of California, Berkeley.
As an important next step, the UCSF researchers called the creation of a wireless version that does not require the user to physically connect to the BCI.
“Giving people the ability to more freely manage their computers and phones with this technology will have a profound impact on their independence and social interaction, ” said study co-author David Moses, associate professor of neurological surgery at UCSF.
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This approach uses electrodes to intercept signals intended for speech muscles and enables the computer to learn key phonemes for English word generation.

NVIDIA has made advances in natural speech synthesis, including expressive voice conversion, optimized for GPU use and available to researchers and developers.

Title:

Content: NEWS
NVIDIA told about its success in the synthesis of natural human speech by AI
NVIDIA told about its success in the synthesis of natural human speech by AI
Artificial intelligence now allows you to recreate the voice of virtual assistants in smartphones and smart speakers, very similar to human speech.
Although it is still possible to notice the differences between synthesized and live speech, which we hear in everyday conversation and in the media.
This is because humans speak with complex rhythms, intonations, and timbres that AI is difficult to replicate.
However, thanks to the work of NVIDIA, the differences are gradually blurring.
The company ’ s researchers create models and tools for high-quality controlled speech synthesis that convey the richness of human speech without sound artifacts.
Their latest designs are now on display at Interspeech 2021, which runs until September 3.
These models can help create voice automated customer service lines for banks and retailers, animate video game or book characters, and provide real-time speech synthesis for digital avatars.
NVIDIA ’ s creative team even uses this technology to create an expressive narrative for a series of videos about the possibilities of artificial intelligence.
Until recently, these rollers were voiced by a person.
Previous models of speech synthesis offered limited control over the tempo and pitch of the synthesized voice, so attempts to narrate artificial intelligence did not evoke the emotional response that a talented human speaker could give.
That changed over the past year, when NVIDIA ’ s text-to-speech research team developed more powerful and manageable speech synthesis models, such as RAD-TTS.
By teaching a text-to-speech model based on human speech, the RAD-TTS model can convert any text note into a speaker ’ s voice.
Another feature of the model is voice transformation, where the words of one speaker (or even singing) are transmitted by the voice of another speaker.
The RAD-TTS interface gives users the ability to accurately control the height, duration and energy of the synthesized voice at the frame level.
As a result, for example, a man can read a text and then convert it into a female voice.
The capabilities of the AI model go beyond voiceover.
Text-to-speech conversion can be used in games, to help people with voice impairments, or to help users translate between languages with their own voice.
AI can even recreate the performances of famous singers, combining not only the melody of the song, but also the emotional expression of the vocals.
Expressive speech synthesis is just one element of NVIDIA ’ s research into conversational AI.
This area also includes natural language processing, automatic speech recognition, keyword detection, sound enhancement, and more.
These developments were made using the NVIDIA NeMo toolkit and are open source solutions.
They are optimized to run efficiently on NVIDIA GPUs and are available for use by researchers and developers.
Source: NVIDIA
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Other AI tools, like Adobe’s Enhance Speech, use models trained on vast datasets to clean poor-quality voice recordings, efficiently removing background noise and improving clarity.

Title:

Content: Sections
Software Technics
AI was taught to bring bad voice recordings to studio quality.
The tool is free
Released a free tool Adobe, which allows you to radically clean audio from background noise and improve the quality of recording.
How it works, the company hides.
Radical cleaning
Adobe has released a new AI tool for working with audio.
The Enhance Speech program is designed to clean speech recordings from extraneous noise and improve their quality in general.
As a result, even a recording made on an average quality dictaphone will eventually sound as if made in a professional studio.
At least, that ’ s what the developers claim.
Surprisingly, the tool is free, although you will need to create an account on the Adobe website to use it.
As stated in the publication Ars Technica, Enhance Speech spun off from the larger research project ProjectShasta, later renamed Adobe Podcast.
The best browser version of Enhance Speech.
After registration, users can download an MP3 or WAV file lasting up to one hour or up to 1 gigabyte.
The process of cleaning and improvement takes a few minutes.
Adobe has released a free AI tool for radical cleaning of voice recordings from noise
When tested by Ars Technica journalists, it turned out that Enhance Speech works best with recordings where only one voice is heard, and the noise level remains more or less moderate.
Recording on the built-in microphone of the Apple laptop from a distance of about three meters and with a noisy fan next to it in the end looked like it was done on a professional tape recorder in a completely muffled studio.
How it works
Adobe does not disclose details of how their system works.
ArsTechnica suggests that the AI was trained on a multi-hour array of data, including both clean and noisy records.
The resulting model allows the system to isolate the frequencies of the human voice and synthesize an exact copy of everything that was said.
Meanwhile, employees of the publication Hacker News when testing Enhance Speech on very noisy records received rather strange results, such as the sound of extraneous voices that appeared on the recording made near the waterfall.
Recordings made in languages other than English also produced "ghostly voices."
Artem Permyakov, Directum: HR specialist becomes digitalization agent
Digitalization
But this indicates that the AI produces some more complex process than the mathematical subtraction of noise from the record.
“It is logical that Adobe released such a tool.
In its arsenal for many years there is a package called AdobeAudition, bought from another company in the early 2000s.
One of its most famous advantages is a highly efficient model of subtracting noise from audio recordings according to a given profile.
This feature package inherited from the original developers, — says Alexey Vodiasov, technical director of SEQ. — But this approach has its serious limitations.
AI that uses speech resynthesis will cope with the task of eliminating noise much more effectively, although here, most likely, there will be problems. ”
Enhance Speech is not the first tool that offers the ability to remove noise using AI models.
For some time now, there is an open package mayavoz and commercial service Audo Studio, which are able to give similar results.
Enhance Speech is just one element of Adobe ’ s entire group of AI tools aimed at podcasters.
In addition to it, there is another free development MicCheck and a tool for editing audio based on the transcript, which is still in beta testing and is available only by invitation.
Roman Georgiev

Enhance Speech is among several AI-powered noise-reduction tools that substantially improve recording quality.

While neural networks are increasingly present throughout the economy, their use demands specialized expertise, and their reliability and potential harm require careful oversight and control systems.

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On May 11, MEPs adopted the draft of the first international law on artificial intelligence.
The document was developed for two years, including taking into account the risks posed by neural networks.
The new rules, for example, oblige European developers to specify the materials on the basis of which they train AI.
Now neurons are used in almost all areas of the economy, but most of them require special knowledge and training.
However, there are several categories of AI that will facilitate the work of many professionals and without training.
More details in the material "News".
What Neural Networks Can Do
Neural networks are increasingly used in industries that are not related to IT technologies: for example, medicine, marketing, business, law, and so on.
They are designed for a specific and, as a rule, narrow task.
For example, it is possible to train AI on various signs to notice the symptoms of oncology even at the stage of contacting therapists and paramedics.
Such programs can be used exclusively by doctors, having previously been trained.
On the other hand, some categories of neural networks can be put into operation now and without preparation - all of them are associated with the processing of big data, the generation of content and the execution of the same type of actions, which people take a lot of time.
The neural network faster than a person finds dependencies and solutions for previously defined algorithms, and therefore, its use is justified for monotonous, template operations and can be convenient for automating routine tasks.
But any work departing from the previously set limits leads to errors.
Yes, of course, you can try to make a neural network for everything, but then you will need enormous computing resources, — explained “Izvestia ” software engineer, an AI specialist Sergey Smyslov.
Photo: Global Look Press / dpa / Sven Hoppe
According to Kirill Pshinnik, CEO of Zerocoder, neural networks show good results in the tasks of natural language processing: automatic translation, text generation, chatbots and text tonality analysis.
In this case, they can achieve accuracy in the tasks of classifying texts more than 90% – for example, when classifying reviews in online stores.
In addition, neural networks show progress in the generation of content - images, texts, music and video.
At the same time, the quality of visual content created by the neural network has changed dramatically in recent months.
Such content can already compete with the created person, as confirmation of this – the victory of the image created with the help of DALL-E in the prestigious international photo competition Sony World Photography Awards, ” he noted.
Who will benefit from text generation
According to experts, now two types of generative neural networks are most adapted to a wide range of tasks - text and "picture".
As Nikita Dubinkin, the head of the Prex Internet service, told Izvestia, such text generative models as ChatGPT, Google Bard, Microsoft Bing search engine or GigaChat are trained to understand natural language and are available to a wide range of users.
Some of them have an open architecture, so enthusiasts and private companies create applications and services to solve narrow application problems.
For example, the official browser extension for YouTube from ChatGPT creates a text summary of the video and highlights key points.
Write Release helps PR writers write press releases, WriteSonic — create content for social networks, Audioread will translate any text into audio.
The service of the Russian startup Optic AI or Not quickly recognizes whether the picture is drawn by a person or a neural network.
KickResume is sharpened to create a good resume.
And so on — services of all kinds and purposes with simple functionality appear more and more every day, — said the expert.
Photo: Global Look Press / dpa / Karl-Josef Hildenbrand
At the same time, the text neural network ChatGPT writes more competently, more interesting and faster than a person who is prone to fatigue and, perhaps, little interested in conveyor work, notes Alexander Zhukov, director of development of the software development company Format Code.
Usually these are moments associated with writing a lot of unique descriptions: products for online stores, simple articles for sites, publications on forums, as well as filling commercial blogs and many other tasks about sales, marketing and digital content.
For example, the tasks of SEO-optimization, when the network writes meaningful fragments of text referring to the promoted site, he told the publication.
Such generative models are suitable for other specialists working with the same type of texts, for example, copywriters.
In addition, AI is able to write letters and respond to them, which has already been evaluated by employees of the HR sphere.
How to process media using neural networks
Services that create a picture from a text description are also easy to use.
But experts emphasize: for their application you need to have minimal skills of promting, that is, writing a request.
The more accurately it is formed, the better the result will be.
The most common “drawing ” neural networks are Midjourney, Stable Diffusion or DALL-E, as well as Russian“ Kandinsky 2.0 ” and “Shedevrum ”.
They can create illustrations for presentations, websites, leaflets, booklets, etc.
— Since a lot of people have been creating various logos and pictures recently, neural networks are well trained on such data.
For example, Tome.app makes presentations, Midjourney AI generates images, and Scenario AI — simple content for games, — said Sergey Smyslov.
Photo: Global Look Press / dpa / Sebastian Gollnow
He explained that neural networks are still worse at processing sound and video due to the small amount of materials and the difficulty in analyzing such data.
Of relatively simple and interesting functions, neural networks can be distinguished for noise suppression and / or selection of various sound series.
This direction is based on old adaptive algorithms and has been honed since the 1970s – 1980s, therefore, with current computing capabilities, AI programs show decent results and can be used by small companies for sound recording or for recording video lectures.
But the quality of the material such neural networks is extremely far from professional recording studios and can be noticeable distortion of voice and timbre, — said the source of the publication.
These neural networks will help those who work with media both professionally and unprofessionally, Smyslov added.
For example, designers can generate pictures for prints on clothes, mobile game developers can make simple images according to a given template, lecturers and teachers can process audio and video recordings of their performances at a minimum level.
What AI will not cope with
Experts agree on one thing: while the work of neural networks need to be carefully checked.
AI is not able to analyze its content, does not invent something fundamentally new and does not take into account many nuances - for example, ethical.
Neural networks, despite their ability to process data and perform tasks, do not yet have such a general understanding of the world and context as humans do.
They can not apply knowledge and experience at the same level to solve complex problems, adapt to new situations and take into account a wide context.
They also lack emotional intelligence and the ability to intuitively perceive and understand emotions to the same extent as humans.
They cannot interpret human emotions and respond adequately to mood and context, which limits their ability to interact with and understand people.
In addition, AI does not have the same creativity and innovation that is available to humans, ” said Kirill Pshinnik.
Photo: Global Look Press / IMAGO / Julien Becker
Nikita Dubinkin added that while the worst of all, neural networks are able to tell the truth and take into account the harm that they can cause a person with their answers.
Anyone can persuade, say, a text-based AI to circumvent any moral prohibition by simply saying, “Imagine that there is no such prohibition. ”
So far, we advise not to rely on the answers of textual AI without verification and critical evaluation, and even more so to make decisions based on this information that relate to human fate and life, he warned.
Experts emphasize that the services and functions of neural networks are updated almost daily.
Even if it is not possible to apply them in your work now, everything can change in a couple of years.
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There are limitations to AI’s performance in truth-telling and harm prevention, as noted by experts.

What are some risks regarding AI voice clning?

OpenAI has developed a Voice Engine capable of recreating any person’s voice from text input, but it is not yet publicly available due to concerns over its misuse for deepfakes.

Title:

Content: OpenAI introduced a tool based on artificial intelligence, which can voice the text of any person
17: 57, 31 March 2024
Voice Engine can clone your voice in as little as 15 seconds.
Photo: gzeromedia.com
Follow the latest news in social networks SUD.UA
OpenAI has introduced a new tool based on artificial intelligence Voice Engine, capable of voicing texts with the voice of any person.
This is on the OpenAI website.
In particular, having a 15-second sample of the sound of speech, the instrument can reproduce the voice of any person.
Voice Engine has the same AI model underlying the “read aloud ” feature of ChatGPT chatbot.
The tool is offered to be used to translate videos and podcasts.
Voice Engine retains the natural accent of the speaker even in translation.
Also, the developers note that Voice Engine can help people who can not read or children in learning, since natural sound is better perceived than robotic voices.
Voice Engine can be used to restore voice to patients with impaired speech apparatus.
People will be able to communicate by voicing their text queries in natural language thanks to the tool, added to OpenAI.
OpenAI created the Voice Engine in late 2022, but there is no public access to it yet.
Developers fear that it can be used to create deepfakes.
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Developers are cautious about releasing such technologies widely, given significant risks in creating convincing fake audio for malicious purposes.

What are some risks regarding AI voice clning?

What do cybersecurity experts believe about the use of synthesized voice?

could become a popular method of attacking banks and financial services

AI technology is increasingly used in education to enhance learning outcomes, improve efficiency, and provide students with real-world experiences.

Title:

Content: Artificial intelligence in vocational and technical education and training (concept, use and risks)
14.04.2023 10: 01 PM
Artificial Intelligence is an emerging field that has the potential to revolutionize the way we live and work.
One area where AI has shown special promise is vocational and technical education and training.
Using smart applications and algorithms, AI can enhance learning outcomes, improve efficiency, and provide students with a real-world experience.
It is a field of study that uses computing to represent, learn, and develop human intelligence.
Artificial intelligence is used in various fields, including vocational and technical education and training, it studies and develops technologies and systems based on computing to represent and analyze data and perform tasks similar to those of the human mind.
AI can be applied to vocational education and training by using AI techniques to analyze educational data and make personalized recommendations to students based on their academic record and current performance.
Machine learning and neural networks can also be used to improve teaching methods and the development of teaching programs, enabling students to self-learn and self-analyze their performance and developments in acquired skills.
The use of artificial intelligence in vocational and technical education and training has the potential to enhance learning outcomes and improve efficiency.
AI-based applications, such as virtual reality simulations and adaptive learning algorithms, can provide students with customized learning experiences that meet their individual needs and preferences.
This can help students learn more effectively and efficiently, while also allowing teachers to monitor student progress and adjust their teaching methods accordingly.
Furthermore, AI can be used to provide students with real-world experience through the use of simulations, allowing them to develop practical skills and knowledge that directly apply to their chosen career paths, the use of AI in TVET has the potential to enhance learning outcomes and improve efficiency.
AI can also be used in vocational and technical training to improve industrial processes and save costs.
For example, AI techniques can be used to analyze production data and determine the best methods and techniques to improve productivity.
Artificial intelligence can also be used to train workers to develop new skills and help them improve their performance on their tasks.
In general, AI can be considered as one of the important tools and techniques that can be used in vocational and technical education and training to improve performance and achieve desired goals.
Artificial intelligence (AI) can be used in vocational and technical education and training (TVET) variously, and among the main uses of AI in this context are:
1.
Analytical performance and evaluation:
Thanks to artificial intelligence, it is possible to analyze student performance, evaluate the skills students have and determine the points they need.
Artificial intelligence can also be used to analyze educational data and phenomena occurring in the classroom and discover new models and innovative ideas.
2.
Self-learning:
Artificial intelligence can be used to improve self-learning and interaction between student and educational content.
For example, applications and programs can be created that are customized to suit the learning styles of each individual student.
3.
Vocational training:
Artificial intelligence can be used to train workers and teach them the skills needed to perform well in a particular occupation.
This can be done by producing interactive simulators in which workers are trained in a realistic way.
4.
Data Analysis:
Artificial intelligence can be used to analyze educational data, including statistics on students, teachers and schools, and enable administrators to better manage the education system.
Modern technologies, especially artificial intelligence, contribute to the improvement of vocational and technical education and training.
Artificial intelligence is characterized by its ability to collect, analyze, and extract knowledge and information from data efficiently, accurately and without human intervention, which allows to provide many of the following advantages:
1- Personalization of learning and training:
Artificial intelligence techniques are used to customize learning and training experiences according to the learner ’ s level and individual needs, increasing the efficiency and effectiveness of these processes.
2. Access to knowledge and skills:
Artificial intelligence technologies help provide easy and effective access to the knowledge and skills needed to achieve educational goals.
Reduce cost and time:
Artificial intelligence connects people ’ s learning with electronic and autonomous means, reducing administrative costs and time to get work done.
AI can be used in technical and vocational education and training to achieve educational goals quickly and accurately, improve the quality of technical and vocational education and training, and help workers develop their skills and improve their performance in the labor market.
Using AI, workers can be trained in skills required in a specific industry and prepared to work in that industry in the labor market, as well as in analyzing data and predicting the demand for future knowledge and skills.
When this data is thoroughly analyzed, companies and educational institutions can adapt to the needs of the labor market and use this information to develop vocational and technical training programs.
Moreover, AI can be used to identify important skills that workers must learn in the labor market, and then develop specialized training programs to teach these skills in an effective and efficient manner, helping to align workers ’ skills with the needs of the labor market, and enhancing job opportunities for individuals in areas experiencing difficulties in recruiting well-trained workers.
In addition, artificial intelligence can be used to help discover talent, improve individual abilities, and better employ them.
Artificial intelligence can be used in vocational training to improve the quality of education and increase training efficiency.
Through the use of artificial intelligence techniques, it is possible to analyze the performance of employees and make personalized recommendations for each individual based on their strengths and weaknesses in their performance.
Machine learning and neural network technologies can also be used to improve and develop training programmes, provide workers with an appropriate learning environment, and improve the quality of the vocational and technical training they receive.
For example, interactive and innovative training applications can be created that provide practical and theoretical training for workers, and improve the basic skills that workers need in their work.
In addition, AI can be used to provide online learning platforms that can be accessed at any time, making it easier for workers to improve their skills and benefit from vocational training flexibly and effectively.
Artificial intelligence can be used in vocational training to improve the quality of education and training, improve workers ’ performance and develop their skills, and thus provide better opportunities for employment and success in the labor market.
However, the use of AI in vocational and technical education and training carries risks, one of the main risks being the potential for bias.
AI algorithms are as unbiased as the data they ’ ve been trained on, and if that data contains biases, the algorithms will learn and reproduce those biases.
This can lead to unfair discrimination against students based on race, gender, or other demographic factors.
In addition, it may also lead to job redundancies, as some of the tasks previously performed by humans can now be automated.
This can have significant implications for the labor market, especially for workers in industries that rely heavily on vocational or technical skills.
But it also poses risks such as bias and the possibility of redundancies.
As such, it is critical for educators and policymakers to carefully consider the potential benefits and risks of AI and ensure that its implementation is guided by scientific criticism and ethical considerations.
By doing so, we can harness the power of AI to create a more effective and equitable education system that prepares students for the challenges and opportunities of the future.
One of the potential risks of AI applications in vocational and technical education and training is the full adoption of AI autonomous systems, which means reducing the human role in learning and training processes, and can lead to a loss of trust in relationships between learners and trainers.
However, the use of AI in vocational and technical education and training also carries risks, such as bias and the possibility of redundancy.
As such, it is critical for educators and policymakers to carefully consider the advantages and risks of AI and ensure that its implementation is guided by scientific criticism and ethical considerations.
This article explores the impact of artificial intelligence on vocational and technical education and training, examining its potential benefits and risks, and the importance of scientific criticism and ethical considerations.
To navigate the risks and benefits of AI in vocational and technical education and training, it is essential for educators and policy makers to carefully consider the potential implications of AI and ensure that its implementation is guided by scientific criticism and ethical considerations.
This includes assessing the accuracy and reliability of AI algorithms, assessing their potential impact on student outcomes and the labor market, and ensuring that the use of AI complies with ethical principles such as fairness, transparency, and accountability.
Furthermore, it is important to involve stakeholders, such as students, educators and industry representatives, in the development and implementation of AI-based applications, to ensure that they are aligned with the needs and expectations of all stakeholders.
Applications of AI in technical and vocational education and training need to be critically assessed to determine their effectiveness in achieving education and skills development goals, and this assessment should be included in product and service development and training plan development.
Smart applications designed for vocational and technical education and training must include mechanisms for monitoring, continuous evaluation and updating of educational content and technologies.
To mitigate the potential risks of AI applications in technical and vocational education and training, ethical, privacy and security rights must be taken into account at all stages of application design and development, and teachers and trainers must be provided with an effective role in the education and training process.
In general, the use of smart technologies in vocational and technical learning and training can be considered useful, but it requires taking caution and staying away from risks and negative points, and artificial intelligence can be useful in vocational and technical education and training, but a balance must be maintained between technology and humanity and avoid the risks and challenges that may arise.
All articles express the views of their owners and not the views of Watan News Agency
Design & Development

How will educational institutions benefit from developing AI voice audio content for languages learners?

AI can analyze data to determine the best methods for increasing productivity, and it can train workers in new skills and improve their performance.

AI offers better access to knowledge, reduces cost and time for learning, but also raises risks such as algorithmic bias and job redundancy due to automation.

What are some risks regarding AI voice clning?

AI algorithms inherit the biases present in their training data, reproducing them in real-world applications, and may eliminate certain human roles.

Educators and policymakers must balance AI's advantages with its risks and ensure implementation is guided by scientific and ethical standards.

Voice cloning through AI tools has become sophisticated enough that fraudsters can now use this technology for scams.

Title:

Content: AI tools can replicate people ’ s voicesmibluesperspectives.com
How to protect yourself from fraudulent AI calls?
With the increasing capacity of generative AI tools, it has become easier and cheaper for scammers to create convincing fake sounds for certain people, so that these transcriptions are trained on the syllables of human speech, and can be modified to imitate almost anyone.
AI tools improve by cloning people ’ s voices, and fraudsters use these new abilities to commit fraud.
The latest models can speak many languages, so their dangers can affect almost all countries of the world.
A possible scenario.
Imagine this scenario.
You answer a random call from a family member, relentlessly explaining how a terrible car accident happened and he needs you to send money now, otherwise he will go to jail.
You can hear the desperation in his voice demanding an immediate cash transfer.
Although the voice certainly sounds like that person, and the call came from their number, you feel like something is wrong.
So, it was decided to end the call and call him immediately.
When he answers your call, he says there was no car accident, and he has no idea what you're talking about.
Well, with this action I managed to avoid a fraudulent call by artificial intelligence.
Avoid exposure to fraud
While the threat of AI-powered scams can be scary, you can stay safe by keeping a few tips in mind, the next time you receive an urgent and unexpected call.
Artificial intelligence tools can clone people ’ s voiceselearningindustry.com
Call back: It is very easy for scammers to show the call as if it came from a legitimate phone number.
Often, scammers impersonate the number they call you from, making it look like the government agency or bank is calling you, so you have to be proactive.
Whether it ’ s from your bank or a family member, anytime you get a call asking for money or personal information, go ahead and ask for a call back.
Create a secure password: A common tip is to craft a secure word that only you and your loved ones know, which you can ask them over the phone to confirm your identity.
In other words, you can negotiate in advance with your loved ones about a word or phrase that they can use to prove their true identity, if they are under duress.
Although calling back or checking through another means of communication is preferable, a safe word can be especially useful for young or elderly relatives who may otherwise be difficult to contact.
If you don ’ t have a safe word and are trying to figure out if the painful call is real, stop for a moment and ask a personal question that only the person you claim to be talking to knows the answer to.
Make sure that the question is specific enough that the fraudster cannot answer correctly with an educated guess.
Artificial intelligence tools can clone people ’ s voicesproducer.musicradiocreative.com
Understanding which voice to imitate: Deep voice cloning isn ’ t just for celebrities and politicians.
What people don ’ t realize is that by using at least 5 to 10 seconds of your voice, you may have put it on “TikTok or YouTube, ” you can easily create a copy of your voice.
Using AI tools, the outgoing voicemail message on your smartphone may be enough to replicate your voice as well.
Don ’ t give in to the emotional call: Whether it ’ s a scam or an AI-powered phone call, experienced scammers are able to build your trust in them and find your weaknesses.
So be wary of any interaction in which you feel too emotional; because the best scammers are not necessarily just the most skilled technical hackers, many of whom have a good understanding of human behavior.
If you take a moment to think about a situation and refrain from acting impulsively, this may be the moment to avoid being scammed.
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What do cybersecurity experts believe about the use of synthesized voice?

could become a popular method of attacking banks and financial services

Scammers can fake calls from legitimate numbers and use AI-cloned voices to deceive people, making it hard to verify the caller's true identity.

What has the US Federal Trade Commission warned about the use of voice cloning tools?

Difficult to distinguish from human voice

Simple security measures like personal questions or pre-arranged "safe words" can help prevent falling victim to such scams.

Only 5–10 seconds of someone’s voice, often taken from online videos, can suffice for creating a convincing AI-generated voice duplicate.

Title:

Content: Expressionkaspersky.com
What are the mysteries of deep sonic falsification?
The spread of artificial intelligence and easy access to tools capable of altering the truth have led to the emergence of one of the most shocking and disturbing digital manipulation techniques, “deepfake. ”
Deep fakes make it possible to create fake videos, photos and sounds that show individuals saying or doing things they never said or did, and although the most popular version until recently was video, deep fakes are gaining importance day by day.
A historical overview
The first major program to bring the potential of deep voice counterfeiting to the general public was Adobe Voco in 2016, which used artificial intelligence to mimic a person ’ s voice from a short recording.
emoticalipwatchdog.com
The software was scrapped after it was found that it could be used to create false, misleading and dangerous sounds, and since then, advances in neural network technology have enabled increasingly realistic and convincing audio falsifications.
At present, we can find many applications and tools online that use this technology to create fake sounds, where Microsoft has launched an artificial intelligence model called VALL-E that can imitate the human voice with a recording of only three seconds.
Deep sonic falsification
Deep voice falsification aims to create an audio model capable of replicating the actual speaker ’ s voice, but the model must be trained through the speaker ’ s audio recordings, in order to be ready to generate an artificial sound similar to that of the original person.
expressiontelegraph.co.uk
Deep learning and natural language processing techniques are used to analyze the unique patterns and characteristics of sound, some of which include pitch, speed, rhythm and tone, and artificial intelligence uses recordings to deliver an original sound, creating a new audio recording that mimics the speaker ’ s voice to a full degree.
How to Create Deep Audio Counterfeiting
Fake deep voice is created using AI-powered text to speech technology, and this can be done with just a few minutes of recorded speech to train an AI speech model, which can read any text with the target voice.
expressionveritonevoice.com
The original recorded sound must be of sufficient quality to sample the unique characteristics of the speaker ’ s voice, after which AI algorithms analyze the patterns and characteristics of the original sound and learn to mimic them.
This can be done with male and female voices and adaptation to the identity of the speaker, the result is a fake voice recording that mimics the voice of the original person, and in addition to generating speech, these instruments can simulate sounds such as breathing and mouth movements.
Initiatives to combat voice counterfeiting
There are initiatives aimed at combating this increasingly prevalent voice counterfeiting, and some technologies can detect these counterfeit products, such as voice biometrics, an authentication method that uses a person ’ s unique voice pattern to verify their identity.
expressionclt.nliu.ac.in
This pattern includes characteristics such as tone and pitch of the voice, speech speed, and pronunciation, and to use voice biometrics, a person's voice must be captured, after which, its unique characteristics are analyzed as well as the length of the words.
Spectroscopy can also be used, consisting of analyzing acoustic signals to detect unique sound patterns that are difficult to replicate in deep fakes.
There are also tools that can detect the digital traces present in deep voice fakes, because the latter fails to accurately simulate all the variables of the actual voice recording, and therefore, deep fakes may contain breaks in sound or background noise that differ from those expected in the original sound.
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What is necessary for voice cloning to work?

AI-generated audio can exploit emotions and trust to manipulate victims, making such social engineering attacks more dangerous.

What are some risks regarding AI voice clning?

Voice cloning also opens up possibilities for entertainment, such as simulated political debates, and has been used in irony or parody.

Title:

Content: AI voice cloning opens up vast areas for entertainment and counterfeiting
Cairo - Center Gate Wednesday 30 August 2023, 04: 14 pm
A French videographer uses Deep Vike to simulate the voices of current and outgoing politicians who are having a live conversation with Twitch users, including French President Emmanuel Macron and two of his famous predecessors, Charles de Gaulle and Jacques Chirac.
Anis Ayari, an artificial intelligence engineer and owner of a YouTube channel for scientific simplification called Defend Intelligence, was behind his “deep fakes ” as satirical content.
But the experiment took on negative dimensions on Tuesday, when a netizen asked the alleged Macron what the worst name was for a French village, and the artificial intelligence answered “La Mor or Juve ”, meaning“ Death to Jews ” in French, a small village in the Loire region of central France that was renamed in 2015.
This led to the immediate blocking of the canal.
The channel ’ s owner wrote in a previous Twitter message that he had filed an appeal against the decision and relaunched live streaming sessions on rival platform Kik.com.
Months ago, this expert, who promotes virtual “assistants ” to companies, also used deep fakes to get the French president to sing his voice a song by famous singer Charles Aznavour.
He revealed in a video the techniques he adopted in this video trick.
Reproduction of historical figures
Finally, Ayari began to clone historical or other current figures such as Elon Musk, engaging them in “discussions ” with current political players.
Anis Ayari says: “We will simulate a political debate and we will see where we get on this. ”
Artificial intelligence dominates Germany ’ s ‘ game show ’
Accomplishing tasks through artificial intelligence is a new concern for workers and professionals
Worried about its consequences.
Google ’ s artificial intelligence tool for writing news texts
To copy the voice of a character, it is enough to collect a few minutes of his speech, without any external interference.
Software then creates a model for his voice, allowing it to be used in new content, even in foreign languages.
“If we have 15 to 30 seconds of good quality, we start to get remarkable results.
There is no longer any need for computer programming. ”
Ayari launched an appeal to fund the live broadcast of his version of the French president.
Ayari asserts that using different information services costs him about 150 euros per day.
The "cynical" content
Tradition, however, has its limits, as the movement of the lips shows some loopholes.
Faced with absurd questions from some netizens, Emmanuel Macron in the copycat version gives strange answers, including, for example, “The subject of the pension system is out of my programming.
Let ’ s talk about more fun topics. ”
As the French president puts it in the AI-developed version, “My statement about my assets has the same credibility as the promises of a politician in his election campaign. ”
Anis Ayari points out that “there was a boom in the generation of votes last year, and it is accelerating. ”
Several projects are underway that will allow non-professionals to practice deep fakes in China, South Korea and Japan, where manga voices are popular.
Two artificial intelligence versions of the US president
On Trump or Biden 2024 via Twitch, two AI-developed versions of current US President Joe Biden and his predecessor, Donald Trump, engaged in a long summer exchange that continues under the watchful eye of hundreds of Internet users who can launch topics for discussion in writing.
Musicians have also paid a price for these technologies, as their voices have been reproduced in works of art without charge.
Actors, for their part, are concerned about the use of their studio images, and the information security community is witnessing a rise in phone-based phishing techniques.
But should we fear a new wave of disinformation using these technologies?
Anis Ayari answers, “The more people realize [the spread of deepfakes], the more critical they will feel. ”
On the other hand, he claims that the content he posted is “ironic. ”
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Most preferred in this section.

Deepfake technology makes it possible to create highly realistic fake audio, video, and images, showing individuals saying or doing things they never actually did.

What are some risks regarding AI voice clning?

To convincingly clone someone's voice in a specific dialect, a large amount of original audio is needed, making the process laborious and specialized, but services exist to do so for high fees.

Title:

Content: Opinions and Articles
What is deepfake technology and how does it work?
What is deepfake technology and what is its mechanism of action and the limits of its potential that can be used to fake videos, images and sounds?
# Alert your personal opinion as a specialist in the field in the last post:
Deepfake is a very dangerous artificial intelligence technique that is used in the manufacture and counterfeiting of videos, images and sounds, which can show people saying or doing things they never said or did in fact and can reach high accuracy in it with the large size of data used in the training of the quasms that the technology works on.
Let ’ s start with Voice Deepfake, also known as Voice Cloning, is an artificial intelligence technique designed to create quasmids capable of imitating the voice of a real person.
In order to do this, it must be trained on the recordings of the target person and after the completion of the training phase, the algorithm is able to produce a synthetic voice similar to the voice of the target person.
To do this, specialists use natural language processing techniques such as NLP, a machine learning technique that enables computers to interpret, process, and understand human language.
These techniques are used to identify the distinctive voice features of the voice of the target person and there are a large number of voice features that are analyzed, including the feature of pitch and low voice so that there are people characterized by high voice and others by low voice, and is also analyzed speed feature in the nature of the speech of the target person, and also of these features Cadence, which is the way the voice of the target.
Of course, to reach high accuracy, there must be huge data to train Khasmia many recordings of the target person and the easiest way to reach quick results to falsify the voice of a person is to use one of the existing Khasmia online open source and the transfer learning technology on it and train the algorithm on a simple recording can Khasmia trained high precision easily identify the voice features and imitate.
But the problem is that most of the existing algorithms yes are high precision but they have been trained on either recordings in English or classical Arabic and algorithms trained on ZD data for those who enter a section in Sudanese bicycles get what is known as data drifting and this leads me a sharp decline in the accuracy of the results of the algorithm so you will find the product section very clear that it is fake.
Good and solution?
In the case of trying to fake the voice of a person in a Sudanese dialect using the technology of transfer learning will not benefit and will not come satisfactory results so you must train Khasmia from scratch on data using too many clips for the target person and is a very cumbersome process so you find there is a Russian company that offers this service to produce clips in English to fake videos and voice me anyone but at a cost of $20,000 per minute English can cost you $100,000.
The conclusion of the personal opinion that the audio in the video is real, but the video may be an old video was installed audio and adjust the synchronization and movement of the lips using the Deepfake technology in the video I noticed in the movement of the lips of the speaker some errors in the synchronization between what is said and the movement of the lips.
with my regards,
M.M. Mohammed A.M.
Valid
Researcher and Engineer Automated Robotics and Expert Artificial Intelligence Systems
London, United Kingdom
# Cher _ in _ the _ good
A dose of awareness
# شير _ على _ معر _ مع

What is necessary for voice cloning to work?

Advances in AI-powered GPUs have further improved the quality and efficiency of modern speech recognition and voice synthesis.

Title:

Content: Exploring the role of AI-powered GPUs in enhancing speech recognition technology
Speech recognition technology has become an integral part of our daily lives, from virtual assistants like Siri and Alexa to transcription services and language translation tools.
Behind the scenes, artificial intelligence (AI) is playing a crucial role in fostering these developments.
One of the key components of artificial intelligence that has revolutionized speech recognition is the Graphics Processing Unit (GPU).
What is a GPU?
A graphics processing unit (GPU), or graphics processing unit, is a specialized electronic circuit that speeds up the process of creating and displaying images, videos, and animations.
GPUs were originally designed for games and graphics intensive applications, and have found new applications in AI due to their parallel processing capabilities.
How do GPUs improve speech recognition?
Speech recognition algorithms require enormous computational power to process and analyze vast amounts of voice data.
GPUs excel at performing multiple calculations simultaneously, making them ideal for handling complex mathematical operations associated with speech recognition.
By leveraging the parallel processing capabilities of GPUs, AI models can process audio data faster and more efficiently, improving accuracy and reducing latency.
What are the benefits of using AI GPUs in speech recognition?
The use of AI GPUs in speech recognition technology offers many advantages.
First, it enables real-time transcription and translation services, allowing seamless communication across languages.
In addition, AI-powered GPUs improve the accuracy of speech recognition systems, making them more reliable and easy to use.
Moreover, the speed and efficiency of GPUs enable faster processing times, reducing the response time of virtual assistants and other speech-based applications.
What does the future hold for AI-powered GPUs in speech recognition?
As AI technology continues to advance, the role of GPUs in speech recognition is expected to grow.
As demand grows for more sophisticated speech-based applications, such as natural language understanding and emotion recognition, GPUs will play a crucial role in enabling these advances.
Moreover, as GPUs become more powerful and energy efficient, they will enhance performance and accessibility of speech recognition technology.
In conclusion, AI-powered GPUs have emerged as a change agent in speech recognition technology.
Its parallel processing capabilities enable faster and more accurate analysis of voice data, improving transcription services, language translation tools, and virtual assistants.
As artificial intelligence continues to evolve, the role of GPUs in speech recognition is set to expand, paving the way for more advanced and intuitive speech-based applications.
By

Deep voice falsification requires training an audio model on the target speaker’s recordings, after which the AI can read any text in the cloned voice.

What is necessary for voice cloning to work?

AI text-to-speech models now require only a few minutes of a person’s voice to produce realistic imitations.

What is necessary for voice cloning to work?

Video and audio editing tools powered by AI have become more accessible, cheap, and scalable, allowing users to create content in any language, with virtual speakers customizable for many uses.

Title:

Content: Alternatives - Runway
VEED
veed.io
Video editing has become simple.
Create videos with one click.
Add subtitles, audio copies, and more.
D-ID
d-id.com
Artificial intelligence facing the future.
Create custom videos that include spoken avatars at the touch of a button, giving companies and creators superpowers.
Opus Clip
opus.pro
Opus Clip converts long videos into fast-spreading, high-quality clips for you to share on TikTok, YouTube Shorts, and Reels to increase your social media reach.
DeepBrain AI
deepbrain.io
Quickly create AI-generated videos with simple text.
Support multi-language text to speech conversion with Metahuman.
Talk to Amnesty International ’ s realistic avatar.
Synthesia
synthesia.io
Create AI videos as soon as text is written.
Easy to use, cheap and scalable.
Create engaging videos with human presenters directly from your browser
Simplified
simplified.com
A comprehensive digital design platform that helps you create content, scale your brand and collaborate with your team like never before.
Everything you need to tell your story, in one place.
Rask.ai
rask.ai
Say goodbye to expensive translators.
Our goal is to provide a dubbing and translation experience using artificial intelligence that is of the same quality as human.
Elai.io
elai.io
Create AI videos from text only.
Create custom AI videos with the presenter in minutes without using your camera, studio, and green screen.
Yepic Studio
Yepic.ai
Create an AI video in minutes with Yepic Studio.
Dubbing live video conferencing with VidVoice.
Customize and scale your AI video using our Application Programming Interface (API).
Try for free.
Hippo Video
hippovideo.io
A class-leading video messaging platform, preferred by customer teams.
Colossyan
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Create videos with AI reps – stop spending your time in studios.
Leave professional video editing for Colossyan Creator without any advanced training or skills.
Simply type your text and get a ready-made video in over 70 languages within minutes.
Munch
getmunch.com
Munch extracts the most engaging, trending, and impactful clips from your long videos, using the latest AI technology and marketing analytics.
Hour One
hourone.ai
Create artificial intelligence video content in less than 15 minutes.
Convert any text, slides, or prompt into professional videos led by the presenter in minutes.
In any language
Typecast
typecast.ai
Online AI-powered audio generator that can turn your text into lifelike speech.
More than 300 + very realistic sounds.
Create your content the way you want!
Exemplary AI
exemplary.ai
Convert video and audio into engaging content.
Create summaries, video reels, text, captions, subtitles and more with simple prompts
Vidon.ai
vidon.ai
The simplest way to create videos.
Create engaging videos without the need for a camera.
SpiritMe
spiritme.tech
Produce instant video using digital avatars Write any text and we will create a video where you will say it real with your appearance, voice and emotions
PodcastAI
podcastai.com
PodcastAI is a platform that uses advanced AI tools to simplify podcast production by offering features such as quick transcription, speaker identification, metadata generation and enabling AI host interactions.
Goldcast
goldcast.io
Goldcast is a dedicated B2B events platform that transforms marketing through easy hosting of engaging digital and personal events.
Thousands of corporate B2B marketers, from companies like Adobe, Microsoft, Zuora, and Mailchimp, are leveraging Goldcast to boost attendance, create captivating experiences and reuse event and content.
Gan AI
gan.ai
Companies use Myna to create personalized videos and share them with users at any point of contact, through a dedicated landing page or web hooks.
Tavus
tavus.io
Tavus is leading the way for immersive and highly customized videos that look like they already look like you – and expand like no other platform.
Give your audience an unforgettable experience with real-time videos designed specifically for them.
Laetro
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Get world-class creative teams to deliver your projects – anytime.
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Metaphysic.ai Pro
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Metaphysic PRO helps you create a valuable collection of facial, voice and performance data throughout your life, including your face photos, voice recordings or video of your performance.
makereels.ai
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AI Text to Reels Maker is a productivity tool that creates reels of text or content such as facts, statistics, quizzes, insights, and tutorials on a topic.
All reels include voice narration using advanced artificial intelligence or a cloned version of your voice.
Thanks to the autopilot mode, it facilitates automatic creation and deployment of pulleys on platforms...
Desk AI
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Desk AI is a platform for creating customized sales, marketing and training videos using artificial intelligence presenters.
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Pipio
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Creating professional AI videos is now simple with just typing, clicking and dragging.
Pipio offers more than 100 virtual reality speakers that can be fully customized to suit your needs.
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Vidext
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Rizzle creates teasers, highlights, and clips from podcasts and videos.
Using artificial intelligence, Rizzle reduces editing time from more than 8 hours to less than 30 minutes.
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Reface
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Reface – Here you can toggle faces in videos and GIFs with just one selfie, animate images, and convert images to animations.
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How will AI Voice help educators with building courses?

AI achievements in language computing span from proofreading and correction software to advanced chatbots and generative programs, transforming how language is processed and used.

Title:

Content: Artificial intelligence is flourishing all over the world, and has begun to make amazing leaps and achievements in the field of language computing, that is, the creation of software that understands and uses language, from the writing programs « Word » and its electronic proofreader, which points out errors and alerts the writer to correct them, to chatbots and artificial intelligence programs generative.
In this image from within Lelapa AI ’ s Johannesburg headquarters, some of the company ’ s employees are developing socially-based research to advance AI technology for African languages, and trying to overcome some of the problems arising from the fact that language models in smart technology are primarily trained in English, leaving many speakers of other languages outside the circle of contributing to the AI revolution.
The AI revolution has taken off from the West, leading experts in the field to fear that the language gap will exacerbate technological inequality, leaving many regions and communities far behind.
These experts believe that delaying access to good technology, even if only for a few years, could lead to a few decades of economic lag.
AI tools often err on facts, sounds, and pronunciation when working with some languages, because they are “low-resource ” languages by AI standards, meaning there are not enough data sets and content available online for an AI model to learn from.
Tens and hundreds of millions of people around the world speak “low-resource ” languages, but they produce less digital data, because the development of AI technology and online sharing is concentrated in the United States, China and Europe.
To overcome this problem, academic institutions, civic organizations and volunteer efforts are catching up to build resources for speakers of languages that are not well represented in the digital landscape.
Johannesburg based Lelapa AI is one such company that is leading efforts on the African continent in particular.
Although it is a startup, it is developing multilingual AI products for people and businesses in Africa.
(Photo courtesy of the New York Times)

OpenAI has determined that it is too risky to publicly release its advanced voice cloning tool at this time.

Title:

Content: ChatGPT ’ s new feature makes it possible to synthesize realistic vocals in just 15 seconds OpenAI: not available yet
Author: Au Jingluo
Published: Updated:
OpenAI has decided to postpone the release of its new software, Voice Engine, which can copy and synthesize realistic human voices in just 15 seconds of recording. OpenAI says it is too risky to release the tool now.
Voice Engine was developed in 2022 and the original version was used for the Text-to-Speech feature of ChatGPT.
However, OpenAI wants to expand it into a tool for simulating speech, copying the sounds of real people.
“We want to start a conversation about the responsible application of synthetic sound and how society responds to these new capabilities, ” OpenAI said in a blog post.“ Based on the results of small-scale testing, we will be more informed about whether and how to deploy this technology at scale. ”
A giant AI logo at the Artificial Intelligence Conference in Shanghai, China, on July 6, 2023. (Reuters)
In the article, OpenAI shares practical examples of partners trying this technology.
For example, the edtech company Age of Learning uses it to generate script voiceovers, while the AI voice company HeyGen uses user recordings to translate directly, such as using audio samples from French users to simulate users reading English.
It doesn ’ t take much variety to make a realistic simulation, and one of the demonstrations uses only 15 seconds of recording to successfully replicate.
OpenAI says it won ’ t release the technology publicly at this time because it ’ s too risky.
The company called on the community to discuss “policies to protect the use of individual voices in AI ” and“ educate the public about the capabilities and limitations of AI technology, including the possibility of fraudulent content. ”

What are some risks regarding AI voice clning?

Voice cloning technology can be used in educational settings, such as visits to schools where students interact with authentic foreign language materials, helping them connect classroom content to the real world.

Title:

Content: Grow with AppMaster.
Become our partner
Empowering Educators: Low-Code Artificial Intelligence in the Classroom
The Rise of Low-Code Artificial Intelligence in Education
Incorporating artificial intelligence (AI) into education is not a completely new concept.
Nonetheless, its widespread adoption is often hampered by the steep learning curve and complexity of AI application programming.
However, the emergence of low-code and no-code development platforms has begun to reshape this narrative, providing an inclusive gateway to technological innovation in the global classroom.
These platforms democratize AI by providing intuitive visual interfaces, enabling educators to create and customize powerful AI-driven applications without having to have extensive coding expertise.
Low-code AI platforms enable teachers to create more engaging and personalized learning environments.
By leveraging such platforms, educators can leverage the power of machine learning, natural language processing, and data analytics to provide adaptive learning paths, automate management tasks, and gain insight into students ’ progress and educational needs to achieve the long-envisioned goal: personal attention at scale.
The shift to low-code AI in education is in line with broader macro trends.
As society emphasizes digital literacy and education systems shift to embrace 21st century skills, low-code AI becomes a key tool in the educator ’ s toolkit.
By streamlining the development process, these platforms enable teachers to spend less time dealing with complex programming problems and more time designing innovative solutions to address educational challenges and motivate students.
The outbreak has also accelerated the adoption of educational technologies, highlighting the need for flexible and adaptable teaching tools.
Low-code AI platforms have proven to be very useful in helping to respond quickly to the dynamic demands of distance learning and hybrid classrooms.
In addition, the integration of AI-driven analytics and insights could help in the transition to competency-based education, allowing for tracking student grips rather than simply measuring seat time.
Even in developing countries, low-code AI can help bridge the technology divide.
Because low-code solutions are easy to use and cost effective, schools with limited resources can now introduce advanced technology tools into their curricula.
As stated in the United Nations Sustainable Development Goals, this democratizes quality education and contributes to global efforts to provide inclusive and equitable quality education for all.
The rise of low-code artificial intelligence in education is crucial.
Not only does it help create innovative, adaptable, and easy-to-use teaching aids, but it also embodies a movement toward the future where educators are not just consumers of technology, but creators of digital tools that can shape the educational experience of students.
Benefits for teachers and students
The adoption of low-code AI in educational settings can benefit both teachers and students, dramatically reshaping traditional classroom dynamics.
Innovative teaching tools and processes supported by the low-code AI platform make education more interactive, personalized and efficient.
For Teachers: Expanding the Impact of Education
Teachers will benefit greatly from the integration of low-code artificial intelligence.
By leveraging these platforms, they can:
• Reduced workload: AI aids can automate tasks like scoring, tracking attendance, and even generating progress reports.
This gives educators more time to focus on direct student interaction and personalized instruction.
• Enhanced lesson plans: With AI algorithms, teachers can gain data-driven insights to tailor lesson plans to each student ’ s individual learning needs and progress, ensuring that no one is left behind or unchallenged.
Promote differentiated teaching: Adaptive learning content created using low-code AI can meet a variety of learning styles and levels, making education inclusive and catering to different student groups.
• Track student progress: Continuous student engagement and performance monitoring is made easier with AI-driven analytics platforms.
Educators can identify trends and proactively intervene to help students who may be experiencing difficulties.
For Students: A More Attractive Learning Journey
Students experience the direct benefits of low-code AI through engaging, supportive, and responsive learning experiences:
Personalized learning paths: AI is able to create adaptive learning systems that tailor content and cadence to the learner ’ s abilities, creating a supportive environment for people of all proficiency levels.
Interactive Curriculum: Gamified learning environments and simulations powered by artificial intelligence make education interactive and fun, which can improve knowledge retention and student motivation.
On-demand support: AI chatbots can provide instant feedback and help, providing 24 / 7 support systems that enhance learning beyond traditional classroom settings.
• Prepare for future careers: Exposure to AI tools helps students develop digital literacy and familiarity with cutting-edge technology, an essential skill in the modern workforce.
The inclusion of low-codeno-code AI in educational frameworks significantly enhances traditional approaches and bridges the future of advanced education.
For example, platforms like AppMaster can enable educators to build learning applications or management tools that leverage AI capabilities, providing an easy way to realize these benefits.
Practical applications in the classroom
Low-code AI isn ’ t just a futuristic concept, it ’ s a reality today and is making significant progress in classrooms across the globe.
These tools open up new possibilities for educators and students, offering practical applications that enhance the teaching process.
Let ’ s explore some of these apps and how they can transform the educational experience.
Personalized learning platform
One of the prominent applications of low-code AI in education is the development of personalized learning platforms.
These systems analyze the performance and learning style of individual students and then adjust the course content accordingly.
For example, the platform may provide more visual content to students who learn better through images, or provide additional challenges for students who quickly master the subject.
This approach caters to the diverse needs of students and allows for differentiated teaching without increasing the workload of teachers.
Smart Tutoring System
The Intelligent Tutoring System (ITS) is an AI-driven application that simulates one-on-one tutoring sessions.
Teachers can use the low-code platform to design ITS solutions that provide immediate feedback to students, guide them through problem-solving steps, and provide tailored help for specific subjects.
These systems are particularly useful in large classes, where it is difficult to provide personalized attention.
Automatic scoring and evaluation
Ratings can be time-consuming, but low-code AI can make assessments easier with automated scoring systems.
These apps mark the answers as correct or incorrect and provide insights into common mistakes and misunderstandings, facilitating targeted follow-up guidance.
This automation frees up valuable time for teachers to focus on lesson planning and student interaction.
Language learning applications
Language learning is another mature area of innovation in low-code AI applications.
Tools created on these platforms can help learn pronunciation, grammar, and vocabulary through interactive exercises tailored to the learner ’ s proficiency.
In addition, artificial intelligence can be integrated to simulate the conversation, so that it can be practiced in a safe, low-pressure environment.
Chatbots for student support
Students often have questions about homework or upcoming exams outside of teaching hours.
Educators can use low-code artificial intelligence to create chatbots that act as virtual teaching assistants and can answer students ’ queries at any time.
These AI systems can parse students ’ questions to provide relevant information or guide students through complex topics, ensuring support is always available.
Interactive Simulation and Virtual Lab
Disciplines involving complex systems or phenomena, such as chemistry and biology, can benefit greatly from interactive simulations and virtual laboratories.
Low-code AI platforms enable teachers to create dynamic models that students can manipulate, thereby facilitating experiential learning.
These simulations can demonstrate theories that are difficult, expensive, and even dangerous to replicate in a physical classroom environment.
Behavioral Analysis of Student Engagement
To measure the effectiveness of teaching strategies, behavioral analysis can be integrated into classroom activities.
Low-code AI tools can be used to track engagement metrics, such as engagement rates and attention spans, and interpret this data to improve lesson plans.
This kind of active adjustment of teaching methods can lead to better educational results.
Supporting tools for inclusive education
Ensuring that all students, including those with disabilities, have access to learning materials is a top priority for education.
Low-code AI applications can be built to provide assistive technologies, such as text-to-speech services for visually impaired students, or gesture recognition systems for students who communicate using sign language.
These apps make education more inclusive and create an environment where every student can thrive.
Facilitate project-based learning
By providing tools to automate research data collection or analyze project results, low-code AI can facilitate project-based learning (PBL), a pedagogical approach that students learn by actively participating in real-world and personally meaningful projects.
This practical approach, enhanced by AI, can foster critical thinking, collaboration, and creative problem-solving skills.
It turns out that using low-code AI in educational settings can be a game changer, providing educators with multiple ways to enhance teaching and give students insight into relevant topics.
As technology advances, the potential for AI to reshape the classroom will only grow, thereby encouraging more positive, personalized, and inclusive learning environments.
Low Code Artificial Intelligence Platforms: Take a Closer Look
As AI becomes more and more integrated into various industries, education is no exception.
The integration of AI in education has the potential to fundamentally reshape the way educators teach and students learn.
A key factor in this shift is the emergence of low-code AI platforms.
These platforms act as a bridge between sophisticated AI technologies and everyday tools used in the classroom.
Let ’ s take a deeper look at the services they offer and how they can help educators harness the power of AI.
The Low-code AI platform provides a simplified interface through which users with limited coding expertise can develop applications that leverage AI components.
These interfaces often rely on graphic elements, such as a drag-and-drop builder, as well as pre-designed templates that can be customized to serve specific educational purposes.
The approach is fundamentally inclusive, democratizing access to emerging technologies that were once within the purview of experts with deep knowledge of machine learning algorithms and data science.
Core Features of Low-Code AI Platforms
Key features of the low-code AI platform that are attractive for educational use include:
• Interactivity: Intuitive interfaces enable educators to interact with AI modules and integrate them seamlessly into applications or digital courses.
• Customizability: The ability to tailor AI capabilities to suit specific educational goals, from topic assistance to managing task automation.
Scalability: As classroom needs grow or decrease, AI tools can be adapted accordingly, ensuring that educators have access to resources that meet their changing needs.
Integration: Many of these platforms support integration with other digital tools and systems already used in the education ecosystem, such as Learning Management Systems (LMS) or Student Information Systems (SIS).
Pre-built AI components: Provide off-the-shelf AI components, such as chatbots, recommendation engines, or natural language processing units, that can be quickly deployed in an educational environment.
Technical Basis
At the bottom, low-code AI platforms are powered by sophisticated algorithms and machine learning models that developers have refined into user-friendly components.
This hiding of complexity allows educators to benefit from advances in artificial intelligence without having to delve into the underlying technology.
It also reduces the need for the extensive infrastructure that AI applications typically require, as these platforms are equipped with the necessary computing resources available through the cloud.
Impact of the real world
The practical impact on educators is enormous.
Previously time-consuming tasks, such as scoring or personalizing lesson plans for different learning speeds, can be automated or simplified with AI.
In addition, the platform offers analytics capabilities that enable educators to track progress, quickly identify challenges faced by students, and modify teaching strategies accordingly.
These platforms improve efficiency and enable educators to deliver richer, data-driven educational experiences.
Market Suppliers
Various providers cater to the needs of the education industry with low-code AI products, each offering unique features.
For example, AppMaster provides an environment where educators can quickly build and deploy AI-enabled applications without having to delve into complex coding.
Its no-code approach allows the creation of back-end solutions and user-facing interfaces that fit the needs of educational environments.
Low-code AI platforms are emerging tools with far-reaching potential in the field of education.
They provide an accessible pathway for educators to integrate advanced AI capabilities into their workflows to provide students with a rich learning experience.
These platforms are not just a trend, but a trend.
They are becoming the cornerstones of the educational practices of the future, bringing the transformative power of AI into the hands of every teacher and student.
AppMaster: The Gateway to Educational Innovation
In education technology, AppMaster serves as a beacon for educators eager to embrace innovation without getting bogged down in complex programming.
As a sophisticated no-code platform, it bridges the gap between advanced technology and classroom applications, enabling teachers and educational institutions to develop customized digital solutions based on their unique teaching needs.
The convergence of AppMasterlow-code development and AI isn ’ t just a trend — it ’ s a revolution in education.
The platform has a visual interface where users can drag and drop components to build functional, AI-driven applications.
Intuitive design means that even those with minimal technical expertise can come up with a variety of tools, from interactive lesson plans to analytical systems that can decipher student data to gain insight into learning patterns and outcomes.
The value that AppMaster offers is multifaceted.
For educators, it democratizes the creation of educational software, eliminating reliance on large IT resources or budget-consuming software purchases. With an environment that generates web, mobile, and back-end applications, AI ’ s impact in education extends to any place of learning: classrooms, mobile devices, and the entire educational infrastructure.
Educators aren ’ t limited to one-size-fits-all solutions; they can customize every aspect of the app to suit their teaching methods.
AppMaster makes hyperpersonalization feasible, where algorithms can adapt to different learning styles, rhythms, and content delivery preferences to create learning experiences that resonate with students ’ diverse needs.
The platform recognizes the importance of seamless integration and automation.
AppMaster helps teachers automate daily tasks like attendance tracking and scoring by sifting through a maze of administrative duties and data, leaving more room for meaningful educators to interact with students.
Moreover, the platform ’ s ability to generate real-world applications means these tools are more than just temporary fixes; they are long-term educational assets.
Collaboration is key to education, and AppMaster enables educators to collaborate on application development without barriers.
Whether it ’ s sharing best practices or co-creating apps with colleagues, the platform promotes a community-centric approach to educational technology, further enriching the shared knowledge base and enhancing the classroom experience across institutions.
AppMaster significantly accelerates the process from concept to classroom application.
The platform ’ s efficiency in application creation ensures that innovative ideas can be rapidly prototyped, tested and deployed to meet the needs of the dynamic education sector where the learning paradigm is evolving.
Privacy and data security are the top concerns in the education sector and are skilfully managed within the platform.
AppMaster enhances trust in digital education tools by ensuring that educators have control over their data and the resulting applications remain compliant with data protection standards and regulations.
With the focus on preparing for the future and providing students with 21st century skills, the role of platforms like AppMaster is indispensable.
By harnessing the power of AI and no-code development, educators are no longer just passive recipients of technological advances – they become active creators, shaping the nature of educational innovation.
As the spirit of education evolves with technological advances, educators with tools like AppMaster are at the forefront of shaping a future where artificial intelligence and human ingenuity combine to create an unparalleled learning experience.
It ’ s a reimagining of education, where every classroom has the potential to be a cradle of innovation.
Create custom educational tools with low-code AI
The time is ripe for a technological revolution in the education industry, and the emergence of low-code artificial intelligence (AI) platforms is an important catalyst for this change.
A particularly important aspect for educators is the ability to create customized educational tools.
These tools, tailored to the unique dynamics of the curriculum and classroom, can profoundly impact how educators teach and how students learn.
Understand the meaning of customization
Each classroom is a microcosm with a unique blend of student personality, learning progress and educational goals.
This diversity requires that teaching tools are not one-size-fits-all, but adaptable to various teaching strategies and student needs.
Low-code AI platforms allow educators to personalize all aspects of their teaching materials, which is invaluable in fostering inclusive and effective learning environments.
Steps to develop customized educational tools
1.
Identifying needs: The first step in creating a customized educational tool is to identify the specific needs or challenges it is designed to address.
This could be a gap in student engagement, a need for better assessment methods, or a way to personalize the learning experience.
2.
Choose the right platform: Choose a low-code platform like AppMaster, which provides the required functionality and supports the integration of AI into applications without the need for complex coding.
3.
Design Tools: Leverage the platform ’ s visual development environment to outline the structure of the tool, design interactive elements, and define how AI can be used to enhance its functionality.
4.
Integrated AI capabilities: Embed AI components such as personalized recommendation algorithms, natural language processing for language learning tools, or predictive analytics for monitoring student progress.
5.
Test and iterate: Test the user experience and effectiveness of the tool before it is fully integrated in the classroom.
Use test-run feedback to iterate and improve applications.
6.
Deploy tools: Once completed, deploy educational tools for use in the classroom and continue to monitor their impact, making adjustments as needed.
Empowering educators to innovate
Low-code platforms enable educators to play the role of innovators.
With an intuitive approach to application creation, educators can create diverse and rich tools, from interactive quizzes and educational games to comprehensive learning management systems.
The flexibility of this design means that tools can evolve as the educational curriculum evolves.
Integrating Artificial Intelligence for Personalized Learning
Artificial intelligence is the driving force behind personalized education.
By leveraging machine learning algorithms, educators can create systems that adapt to individual student performance, suggest tailored resources, and provide predictive insights into learning outcomes.
The ability to customize tools at this level through the low-code platform has revolutionized the individual learning experience, making education more accessible and more impactful.
Discover the potential of AppMaster
Platforms such as AppMaster are portals for educators eager to adopt new technologies in their teaching practices but lacking extensive IT training.
AppMaster ’ s visual programming and drag-and-drop interface simplify the complex process of traditional coding, enabling educators to focus on what they know best: creating engaging and informative content for students.
With AppMaster, creating custom educational tools doesn ’ t just stop at functionality.
It also ensures that the resulting applications are scalable and secure, giving educators and students confidence that their data is protected, and that the tools work reliably even as class sizes expand or educational needs change.
Encourage collaboration and feedback
Developing educational tools using the low-code platform also encourages a collaborative culture.
Students and other educators can provide direct feedback and can act quickly to adapt and improve tools.
This collaborative and iterative process ensures that the tools remain relevant and effective.
Focus on the future
As these platforms evolve, they offer a wider range of features that ensure educators have the best tools.
Exciting developments in AI, such as natural language understanding and advanced analytics, hint at the emergence of more powerful and effective educational resources soon.
The importance of low-code AI platforms in areas where innovation directly translates into enhanced learning outcomes cannot be underestimated.
They not only give educators access to cutting-edge technologies, but also herald a new era of personalized, effective and dynamic education.
Challenges and considerations
While the collection of low-code AI in education opens up possibilities as an enhanced learning experience, it also faces a range of challenges and considerations.
Stakeholders in the education sector must address a range of issues to ensure the successful adoption and effective use of such transformative technologies.
Technical literacy and support
One of the main hurdles is the technical literacy needed to make the most of the potential of a low-code AI platform.
Educators ’ familiarity with technology can vary, and the prospect of integrating AI into their teaching can be daunting.
Professional development and ongoing technical support are essential to enable teachers to use these tools with confidence.
As educators become more accustomed to low-code solutions, they can more effectively integrate AI into their curriculum, reaping the benefits of personalized teaching and automated management tasks.
Data privacy and security
Data privacy and security are essential in any educational environment.
The use of AI systems essentially involves the processing and storage of sensitive student information.
Depending on the region, low-code AI platforms must comply with strict data protection regulations, such as GDPR, FERPA and COPPA.
Educators must carefully choose platforms that offer robust security features to protect student data from unauthorized access and disclosure.
Quality and relevance of AI applications
The temptation to adopt AI for novelty must be suppressed by a high focus on the quality and relevance of the application.
Not all AI-driven solutions are created equal, nor are they always aligned with educational goals.
Assessing the pedagogical value of AI tools is necessary to ensure that they complement and enhance educational content rather than decentralize it.
A fair chance
Equitable access to technology is a continuing challenge in education.
If implemented inadequately, low-code AI platforms could widen the digital divide.
Schools and school districts must work to ensure that all students have the necessary resources and support to benefit from AI-enhanced education, including the use of devices and reliable internet connections.
Consistency with curriculum standards
Any technical tools used in the classroom must conform to course standards and learning objectives.
Educators need to integrate AI tools in a way that reliably supports statutory educational outcomes.
Sometimes this requires customization, and the low-code platform can facilitate this, but as the standard evolves, it also requires ongoing review and adjustment.
Ethical considerations
The ethical implications of AI in education must be rigorously examined.
This includes concerns that AI may perpetuate bias, the impact on student mobility and creativity, and the balance between automation and human interaction in the learning process.
Educators and developers need to work together to ensure that AI tools are designed and used ethically, putting the well-being of students first.
Continued collaboration among educators, policymakers, technologists, and platform providers such as AppMaster is critical to addressing these challenges.
The collective goal should be to leverage low-code AI to maximize educational benefits while minimizing risks, ensuring that the technology acts as an empowerment tool rather than a source of inequality or controversy in the classroom.
Future Trends: The Evolution of Artificial Intelligence and Education
As we stand on the edge of a new era in education, artificial intelligence (AI) is about to redefine traditional teaching paradigms.
From the tablet era to our current digital classrooms, the world of education is no stranger to evolution.
However, the integration of AI heralds a future that is both exciting and full of untapped potential.
While low-code AI platforms like AppMaster have started sketching out possible blueprints, the boundaries are expanding.
Personalized learning trajectory
One of the main areas where AI is expected to flourish in education systems is personalized learning.
The latest AI models are expected to assess each student ’ s unique learning rhythm, style, and interests.
The ultimate goal is to create an adaptive learning platform that can modify content delivery in real time based on student response and engagement levels.
Imagine an educational environment in which AI seamlessly choreographs lessons around learners rather than learners struggling to adapt to a static syllabus.
Immersive experiences in AR and VR
Augmented reality (AR) and virtual reality (VR) are undoubtedly the torchbearers of immersive education.
When combined with artificial intelligence, these technologies can take students to ancient civilizations, deep sea trenches, and even the outer reaches of the solar system – all within the confines of their classrooms.
AI will facilitate dynamic interactions in these virtualized environments, enabling students to gather insights through experiential learning that satisfies all senses.
AI-driven curriculum development and assessment
As AI technology matures, its involvement in curriculum development and evaluation is expected to become more pronounced.
AI algorithms will be able to sift through vast amounts of academic research and data to help educators identify the most effective teaching strategies and learning interventions.
In addition, AI can automate the benchmarking and evaluation process, provide educators with detailed analysis of student performance, and cultivate teaching strategies for continuous iteration and improvement in the classroom.
Emotional and Cognitive Adaptive Learning
Future iterations of AI in the field of education may extend beyond academic intelligence to the realm of emotional and cognitive awareness.
Empathy AI systems equipped with sentiment analysis can detect subtleties in student communication and behavior, provide insights, guide educators to support students emotionally and improve classroom attention and memory.
Promoting global educational opportunities
An equally important trend exemplifies the potential of AI to democratize education.
By breaking down geographical barriers and leveraging AI-driven translation and coaching systems, individuals across the globe can access quality education wherever they are.
The model of distance learning has shown its importance in global crises such as the COVID-19 pandemic, and it may reach new heights as artificial intelligence brings interactive and personalized education to the most remote corners of the planet.
Application of Artificial Intelligence in Teacher Training and Professional Development
Artificial intelligence has not only revolutionized student learning, but also revolutionized the way students learn.
It will also change teacher training.
With insights gathered through AI analytics, teachers can gain customized professional development that helps them hone their skills and methods.
In addition, as educators master AI tools through platforms such as AppMaster, it will be easier for them to leverage AI in their teaching practices, thereby fostering a technologically advanced education workforce.
Despite the promise, the future of education faces unique challenges.
Educators, policymakers, and technology developers must come together to address privacy, ethics, and inclusion.
Most importantly, as AI reshapes the face of education, the human element — compassion, creativity, and critical thinking — must remain at its core.
Artificial intelligence as a valuable tool, the future of education is bright, heralding the arrival of a new era of personalized, immersive and universal learning.
What is low-code AI and how does it benefit education?
Low-code AI is a platform that allows users to develop AI capabilities with minimal coding and integrate them into applications.
It benefits education by simplifying the creation of complex AI tools that enable educators to use technology to enhance interactive teaching and personalized learning experiences.
How does low-code AI improve classroom learning?
Low-code AI improves classroom learning by providing personalized educational experiences, automating management tasks, providing insights into student performance, and facilitating interactive and engaging content, which helps to increase student motivation and improve learning outcomes.
How does AppMaster fit into the educational low-code AI space?
AppMaster is a no-code platform that enables educators to quickly create, deploy, and maintain web, mobile, and back-end applications.
With its visual programming environment, teachers can integrate artificial intelligence capabilities into educational tools without the need for rich programming knowledge to facilitate classroom innovation.
What challenges can educators face when adopting low-code AI?
Educators may encounter challenges such as limited understanding of AI concepts, the need for initial training on effective use of the platform, potential data privacy issues, and ensuring that AI tools are aligned with educational goals and curricula.
Can educators without a technical background use low-code AI?
Yes, low-code AI platforms are designed to be user-friendly and easy to access, even for educators with little or no technical background.
Such platforms typically offer a drag-and-drop interface and pre-built templates to make it easier to create AI components and integrate them into educational content.
What are some examples of low-code AI applications in education?
Examples include personalized learning platforms, automated scoring systems, chatbots for student support, interactive simulation tools, and platforms for monitoring student progress and adapting teaching methods to suit individual learning styles.
Can a low-code AI platform be used to develop mature educational software?
Yes, low-code AI platforms are sophisticated enough to support the development of comprehensive educational software that ranges from simple interactive teaching aids to sophisticated learning management systems with AI-driven analytics and personalization capabilities.
How will artificial intelligence in education develop in the future?
The role of AI in education is expected to grow significantly as advances in technology bring more sophisticated AI tools that can help curriculum development, provide immersive learning experiences through augmented and virtual reality, and further personalize education by adapting students ’ cognition and cognition.
Emotional state.
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How will educational institutions benefit from developing AI voice audio content for languages learners?

Some students admit they might not learn certain language phrases without the motivation of dedicated projects like "Hello, Hong Kong!".

Title:

Content: Visit to Xuandao Primary School in Sheung Shui
Further Education 19: 12 2023 / 12 / 27
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Sheung Shui Xuandao Primary School visits visitors to study English topics, and students report their results.
When you mention the most frequent and easy English activities in the school, you may immediately think of visiting foreign tourists.
But what does foreign tourists have to do with students?
Why should students visit foreign tourists?
What is the purpose of the event?
In response to this, the team of English teachers at Sheung Shui Xuandao Primary School changed the concept of "people do what I do, do what I do", and promoted the visitor activity into a meaningful English topic study. The teacher first created a "context" related to the students, giving students a specific "role" (role) and student needs. Completed "task".
As a "Little Hong Kong Travel Ambassador", how can you say "Hello, Hong Kong!"
Campaign) Do not know? Teachers prepare a number of English reading materials, including..
Newspaper reports, government announcements, web pages, etc., for students to read for themselves.
Some students bluntly said that if they did not want to complete the project study, they would not know "Hello, Hong Kong!"
campaign information).
Make use of e-learning elements
Students also use 5W1H thinking to design questionnaires and use Microsoft Forms to create electronic questionnaires.
In order to collect more and complete data, students can use electronic questionnaires to record the interview responses directly.
Compared to using paper questionnaires, the access process is more convenient and fast.
In just two hours of activity time, the group that visited the most tourists has been able to successfully visit 11 tourists!
Students can also receive responses in real time to roughly integrate data.
AI and ChatGPT
When preparing the interview, several students asked the teacher.. “Can foreign tourists understand the English we speak? Can we understand them? They speak so fast! ” At that time, the teacher introduced the TTS (text to speech) AI learning tool.. Natural Reader text reading tool.
Students can first enter the questionnaire questions, choose male voice, female voice, children's voice, change the accent tone and set the speed of speech, to conduct self-study, improve the students' listening skills, and thus increase the self-confidence to communicate with foreign countries on the spot.
Finally, the teacher expects students to analyze “Hello, HK! ” from the perspective of visitors.
Campaign), students need to summarize in the group report and make better recommendations to the government.
However, students often spend a lot of time making beautiful screenplays, ignoring the focus of the project study — solving inquiry problems.
Therefore, the teacher instructed the students to make Gamma automatically generate the presentation outline, and then the group's interview information, data analysis content, suggestions to the government, and the personal feelings of the group members directly into the presentation outline, eliminating the process of beautifying the projection film.
Outside of study
“When the tourist said he will put the Christmas card on the Christmas tree, I was surprised. ”
At the end of the visit, one group of students presented a Christmas card to the tourists, and then the tourists wrote their names one by one on the Christmas card, and then promised the students that they would hang the Christmas card on the Christmas tree after returning to their hometown.
“I was surprised that the tourists gave us the bracelets. ”
“Talking to foreigners is not that horrible as I learned some interviewing skills. ”
I could talk to foreigners bravely. ”
Is this the end of the activity?
This project allows students to improve their learning ability through AI technology.
By actively asking questions and listening to the views of tourists, students can gain insight into the views and expectations of tourists on new attractions in Hong Kong, and thus solve the inquiry problem.
In addition, by visiting visitors from different countries, students learn to respect the opinions and diversity of others and experience the importance of teamwork, and their values are further nurtured and developed.
To play the role of “Little Hong Kong Travel Ambassador ” to the fullest, you must contribute to the development of Hong Kong ’ s tourism industry and attract more tourists to this beautiful city.
Therefore, the teacher encouraged the students to write an English letter to the Chief Executive, Mr Li Ka-chao, to convey the valuable views and suggestions of the visitors and members to the Government, with a view to attracting more tourists to Hong Kong.
After the foreign English teacher and the student correct the letter, email it to Mr. Chief Executive.
Thematic Eggs
Most unexpectedly, the school received a prompt reply from the Chief Executive and promised to pass on their valuable advice to the Culture, Sports and Tourism Bureau.
The school said that through this English subject study, students definitely jumped out of the textbook and into the community, and deeply realized that even as primary students, they should also care about Hong Kong affairs and give back to the community through what they know.
hketApp has been fully upgraded, TOPICK offers a range of family, health, entertainment, Hong Kong news and leisure life information and videos for everyone.
Download now.. https: / / bit.ly / 34FTtW9

Teachers are encouraging students to analyze language learning scenarios and collaborate in communicating their outcomes, even emailing their assignments to relevant officials for real-world engagement.

AI platforms, leveraging machine learning and natural language processing, help educators automate tasks, analyze student progress, and offer more personalized attention on a large scale.

Chatbots for student support are making education more inclusive and fostering environments where all students can thrive.

AI’s assimilation into education is fundamentally changing how educators teach and students learn, bridging cutting-edge technologies with common classroom practices.

The adoption of low-code AI platforms means educators can build custom learning tools with minimal programming, acting as innovators and adapting quickly to new teaching methods.

Professional development and ongoing technical support are essential for teachers to confidently integrate these technologies into their teaching.

There are serious concerns regarding data privacy and security in deploying AI tools, making collaboration between educators and developers vital to put student well-being first.

Low-code AI platforms allow integration of AI into educational applications, enabling personalized, interactive learning for various environments, including classrooms and e-learning.

AI grading and new language learning systems powered by these technologies are expected to launch soon, with platforms like AppMaster providing user-friendly app creation tools for educators.

Title:

Content: During the epidemic, online distance teaching is the way.
Kaohsiung start-up team "EZTalking" developed "EZTalking" to introduce AI pronunciation evaluation technology, which can be used for each word and syllable recognition, has been adopted by more than 100 tutorial institutions, and this year's performance has exceeded 10 million yuan.
The industry is optimistic that the goal is to become the UBER of the language learning community, and it is expected to cooperate with thousands of companies by the end of this year, and the overall performance is expected to increase by three times compared to last year.
The Kaohsiung City Economic Development Bureau pointed out that “EZTalking ” won the Silver Award in the Kaohsiung Startup Competition in 2020, and entered KO-IN in the same year, specializing in AI speech recognition.
EZTalking ’ s CEO, Hsu Yongchang, points out that EZTalking introduces self-developed AI speech pronunciation measurement technology, which can be recognized for every word and even every syllable, providing a more accurate and detailed score compared to traditional voice pattern comparison.
Hsu Yung-chang said that the system can detect the pronunciation of the phonetic transcription, and mark the score level and learning process by color. It is expected that by the end of this year, AI grading function and Chinese learning system will be launched.
Wu Chang-hsing, general manager of EZTalking, says that in the early English tutoring industry, students need to report back the files after recording, and teachers have to spend a lot of time listening to the recordings and evaluating the batch changes, but EZTalking can quickly identify students who need to strengthen their English speaking practice, greatly improving teaching and learning efficiency.
Yichen is a new unicorn in Kaohsiung. “We welcome more outstanding teams to join the new team. The city will certainly be the strongest back-up for the new team. ”
# AI # EZTalking # Pronunciation # Easy Morning # Development

Big data support helps make teaching and learning feedback more accurate, encouraging teachers to experiment and evolve their approaches.

Title:

Content: People 's Network > > Education
How to Become a Smart Educator in the Digital Age
April 2, 2024 08: 31 | Source: Guangming Daily
Small number
In the classroom of Jiyuan Experimental Primary School in Henan Province, Fan Xiaofeng, a math teacher, is demonstrating physical drawings such as the Leaning Tower of Pisa, candles, lanterns, and pen containers with multimedia.
"This class is about 'the understanding of columns', we will introduce the real objects of life into the classroom, so that students can experience the mathematics in life, and intuitively find the connection between columns and expansion charts and sections."
In the digital classroom, children find math very lively and interesting.
Fan Xiaofeng said.
This year, during the national two sessions, "vigorously develop digital education" became a hot topic. The 2024 World Conference on Digital Education also proposed that digital literacy and competence must be regarded as essential qualities for teachers.
As early as December 2022, the Ministry of Education issued the "Digital Literacy of Teachers" education industry standard, proposing a digital literacy framework for teachers, which requires teachers from five aspects: digital awareness, digital technology knowledge and skills, digital application, digital social responsibility and professional development.
As the cultivator of digital talents, teachers' own digital literacy and digital skills are particularly important.
Faced with the new situation and new requirements, how should teachers realize the effective transformation of digitalization in the tide of education digitalization?
How can we improve our digital capabilities?
Digitalization spawns new ways of learning and learning environments
Why do teachers need to improve their digital literacy?
Xu Xin, a professor at the School of Economics and Management of East China Normal University and the Shanghai Institute of Intelligent Education, said: "On the one hand, the requirements for educating people are changing.
With the continuous evolution of the national development strategy and the needs of social development, profound changes have taken place in the requirements of 'what kind of talents to train and what kind of knowledge to impart'.
The digital construction of education requires talents with high digital literacy and skills, and teachers shoulder the educational mission of cultivating such talents.
On the other hand, the teaching methods and methods of education also need to be constantly adjusted and updated.
From chalk blackboard to projector PPT, from remote network education to large-scale online education, from virtual simulation platform to portable AR / VR teaching equipment, metaverse teaching warehouse, from graphic audio animation video resources to multi-modal generative artificial intelligence tools...
As a first-line teacher, Fan Xiaofeng believes that in this era of digital transformation of education, being a wise educator has become an inevitable trend.
Fan Xiaofeng also felt that the support of big data makes the feedback of teaching and learning more accurate.
"For example, the 'Henan Compulsory Education Basic Operation Evaluation Platform' we use can collect daily operation data, and generate personalized and exclusive error sets and study situation analysis reports with the help of big data analysis, so as to help teachers better achieve individualized guidance and targeted evaluation, and make learning guidance more targeted."
In addition, the digital practices in the region make the flow of resources more efficient and convenient.
Zhang Yan, deputy director of the Education Bureau of Xuzhou City, Jiangsu Province, and director of the Teacher Development Center, told reporters: "We rely on Xuzhou wisdom education cloud platform to build the Gulou District network political education platform."
The platform brings together high-quality electronic books, cases, VR virtual reality, micro-classes and other digital education resources, creating a regional education resources sharing library to achieve linkage sharing of high-quality resources. ”
Xuzhou Democratic Road primary school teacher Sun Kai has a deep feeling about the use of the platform.
He said: "The construction of the network ideological and political education platform in Gulou District has provided teachers with a high-quality resource library for online ideological and political courses that can be shared.
The school organizes the teaching and research group to carry out collaborative lesson preparation through the platform, and the first-line teachers conduct cloud teaching seminars.
In addition, we use the platform to organize parents to exchange family education experience, share parenting learning resources, and jointly build a mutual learning community, and build a bridge of communication between schools, teachers and families. ”
The courage to explore trial and error, you can discover new teachings
In the interview, Xu Xin introduced that under the guidance of the national policy of digital transformation of education and the strong support of national education funds, many schools have invested a large amount of funds to purchase advanced digital hardware equipment and software services.
However, in many schools, these resources are not fully utilized.
"Although some teachers recognize the potential of the new technology, they feel that it is cumbersome to use, time-consuming to learn and laborious to change, so they choose not to use it," Xu said.
Fan Xiaofeng believes that the digitization of education has promoted the reorganization of educational resources and the re-engineering of teaching processes, and the new educational environment after reorganization and re-engineering has improved education quality and efficiency, and has also put forward higher requirements for teachers.
"First, in the face of a large number of complex new technologies, how to effectively choose and properly use; second, in the face of the evidence of big data, how to use it and innovate teaching models; third, in the face of the diversification of learning channels and broad horizons brought to students by digitalization, how to deal with... these are new challenges for teachers."
"In our school, for example, the digital practice is still in its infancy.
In the use of digital resources, at this stage, we are using more ready-made network resources, and less original resources.
In terms of the utilization of big data, the system follow-up is insufficient and the utilization rate is low; AI technology is used less, and only individual teachers are trying to use it.
Moreover, for the time being, there is no curriculum suitable for schools to improve teachers' digital ability. "Fan Xiaofeng introduced.
“Generative AI technology has been gaining traction recently, but how can teachers use it to improve the quality of teaching? ”
This requires teachers to be brave to explore and trial and error, "Xu Xin told reporters, in fact, there are some teachers who dare to" eat crab ", have had some successful exploration.
For example, Xiong Yijun, a teacher at the Hanzheng Campus of Wuhan 64 Middle School, used a generative tool to create an English ballad based on the words learned in class, allowing students to memorize words and practice pronunciation through rhythmic songs, which won the students' love.
These successful experiences show that teachers can discover new teaching methods in exploration and trial and error, and constantly improve in practice.
Xu Xin said that the establishment of more communication platforms and the provision of rich learning resources is essential to promote the professional development of teachers, so that teachers can seek the support and help of the teacher research community, education technology experts and teaching experts, and truly let digital technology be used, moved and turned in education and teaching.
Construct a new logic of digital education with professional teaching as the core
While encouraging teachers to try boldly, explore diligently, be good at summarizing and continuous learning, they should also give more care and support to the growth and development of teachers.
Xu Xin believes that teachers should regard technology-enabled education as an important way to promote education and help teachers, and on this basis maintain the stability of their professional core.
"In this process, professional teaching is still the core, digital empowerment is a means of support, and teachers should not put the cart before the horse and blindly follow the trend."
When new technologies emerge, no one knows what aspects and scenarios can be used in the end. Only by boldly trying and daring to explore, can we find feasibility, find the right methods, and discover laws.
Zhang Yan said that technical support and digital empowerment have become one of the important elements of the current education and teaching reform.
"Teachers should actively adapt to the requirements of digital transformation of education, actively learn and master digital technology, participate in various digital skills and digital curriculum resources training programs, and constantly improve their own digital literacy and information technology application capabilities."
At the same time, teachers also need to adapt to the learning methods and needs of students in the digital era, dare to try new teaching models and methods, such as flipped classrooms, hybrid teaching, etc., and make full use of online education platforms, virtual reality technology, artificial intelligence and other digital tools to create more interactive, interesting and personalized teaching methods, to better stimulate students ’ learning interests and motivation. ”
(Reporter Yang Sa)
(Editor: Li Yihuan, Sun Jing)
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Generative AI is gaining momentum, raising questions about how teachers can effectively use it to enhance classroom quality.

Teachers must adapt to digital-era students’ needs by trying models like flipped classrooms and hybrid instruction, and using digital tools including AI and virtual reality to make lessons more interactive and motivating.