**NUGGETS SUMMARY: VOICE CLONING & AI-GENERATED SPEECH TECHNOLOGY**

**1.

What is Voice Cloning Technology?

**
- AI-powered voice cloning and text-to-speech (TTS) tools can now generate realistic, human-like voices in dozens of languages using minimal audio samples (sometimes as little as three seconds).

- These systems analyze a speaker’s vocal patterns, timbre, accent, and intonation, then reproduce natural-sounding speech in multiple languages—sometimes making it possible for someone to “speak” a language they don’t know.

How is it Developed?

**
- Technological advances, such as those from ElevenLabs and Meta AI, often rely on large AI models trained with vast banks of spoken and written language data.

- To improve fidelity, data from both written and spoken resources are used, sometimes with paired sentences or crowd-sourced contributions.

- Continuous improvement is the norm; these systems adapt and enhance performance over time as more user data is integrated.

Applications and Use Cases:**
- **Entertainment:** AI voice cloning creates alternate reality media (e.g., famous people speaking unfamiliar languages or performing songs they never recorded).

- **Accessibility:** Fast, consistent translation and dubbing open new possibilities for accessibility, such as AI-dubbed documentaries (China Media Group), AI language tutors (Loora), or real-time translation for spoken-only languages.

- **Marketing & Business:** AI-voiceover and video tools like Vidnoz AI allow rapid content localization, lip-syncing, and message customization across languages.

- **Education:** Language learning benefits from natural-sounding, customizable AI tutors that adapt to accent and topic.

- **Negative Uses (Scams):** The same fidelity used for positive applications enables deepfake scams—fraudulent calls or messages using cloned voices of family members or officials.

Legal and Ethical Implications:**
- **Copyright and Consent:** Using someone’s likeness or voice may violate rights of publicity or copyright, especially if done without consent.

- **Fraud and Misinformation Risks:** The capacity for imitation makes phishing, impersonation, and disinformation campaigns more accessible and credible.

- **Data Security:** Training these models can raise concerns about how voice samples are obtained, stored, and protected.

- **Equity & Bias:** The technology may not equally represent all languages or dialects, possibly marginalizing underrepresented groups.

- **Brand Consistency vs.

Manipulation:** While brands value consistency, tools could create unauthorized messages or content.

Real-World Examples:**
- AI-generated songs featuring famous voices not authorized by those artists have gone viral.

- Companies are raising funds for AI tutors that claim to rival real human engagement.

- AI-dubbed documentaries and cross-lingual marketing empower global reach.

- Scams using cloned voices (e.g., fraudulent calls “from” family members) have already been reported.

Ongoing Challenges:**
- Technology is advancing rapidly—day by day, not year by year—so regulation and ethical frameworks must keep pace.

- The balance between innovation, creative use, and responsibility remains critical, especially where consent, authenticity, and impact on employment are concerned.

- Users, businesses, and educators are urged to stay informed, consider ethical ramifications, and advocate for responsible use alongside legal compliance.

**Conclusion:**
Voice cloning technology delivers powerful tools for communication, education, and content creation but also demands vigilance regarding privacy, consent, security, and authenticity.

Both its creative and deceptive potentials are growing as rapidly as the technology itself.

**Nuggets of Information from the Extract on AI and Voice Technology in Education & Beyond:**

- **AI in Course Creation:**
  - AI speeds up educational product/curriculum development – course structure generation can take minutes, with later human revision and expert review.

- AI can generate texts, suggest titles for courses or long-form materials, and assist throughout lesson design (tools such as ChatGPT, TurboText, Webcanape, and WebX).

- Quality control is crucial; over-reliance on AI may lead to a flood of low-quality, untested courses.

- **Voice and Audio AI Applications:**
  - Neural networks can now realistically synthesize natural human speech from text, allowing for “natural” sounding AI voices.

- Text-to-speech tools are highly accessible; users simply provide text and receive a realistically voiced audio output.

- Major companies (Google, Meta, Amazon, NVIDIA) invest heavily in speech recognition and synthesis, using advanced models optimized for efficiency on specialized hardware (like NVIDIA GPUs).

- **Medical and Accessibility Innovations:**
  - AI-driven brain-computer interfaces are enabling new methods of communication for individuals with severe disabilities (e.g., stroke patients can “speak” via AI-powered avatars that decode brain signals into speech).

- Fewer phonemes are required for these systems to decode language, making communication more efficient for non-verbal individuals.

- **Audio Enhancement Technology:**
  - AI tools (e.g., Adobe Enhance Speech) significantly improve audio quality, removing noise and upgrading bad recordings to near-studio quality.

- Free and commercial solutions are available, with increasing accessibility to both educators and the public.

- **Voice Cloning:**
  - AI can mimic any individual’s voice, converting recorded texts into different voices, even allowing gender or accent changes (important for language learning simulation and accessibility).

- OpenAI has developed advanced voice cloning models (Voice Engine) but currently limits public access due to deepfake concerns.

- **Risks and Ethical Dilemmas:**
  - Voice cloning and audio AI raise serious ethical issues: potential for deepfakes, identity theft, deception, and reputational harm.

- Developers remain cautious, balancing the innovation with risks (e.g.

OpenAI restricts their own technology’s release).

- There is a larger debate about truthfulness, accuracy, and potential harm resulting from AI-generated content.

- **Legal Considerations:**
  - Use of AI for copying or simulating voices is under increasing scrutiny; unauthorized cloning (without consent) may breach privacy, intellectual property, or even criminal law.

- Some uses (accessibility, language learning, entertainment) are encouraged, but the same technologies enable scams and misinformation.

**Summary:**
AI-powered voice generation and cloning technologies have revolutionized curriculum design, accessibility, entertainment, and medical communication.

While educational applications are promising—enabling quick content creation and authentic voice material for learners—significant risks remain in the form of deepfakes, misuse, and insufficient oversight.

Continued ethical consideration, rigorous quality control, and legal safeguards are essential as such tools become more widespread and accessible.

**Voice Cloning Technology: Summary of Key Points**

**What is Voice Cloning Technology?

**
- Voice cloning uses artificial intelligence (AI), particularly deep-learning algorithms, to create digital replicas of human voices.

- With as little as 5–10 seconds of recorded speech, AI can generate highly realistic synthetic voices capable of reading any script as if spoken by the original person.

**How is it Developed?

**
- AI models are trained on large datasets containing audio samples of the target voice.

- Advanced techniques, such as transfer learning and deep neural networks, enable high accuracy, especially when ample training data is available.

- Specialized GPU hardware accelerates the training and deployment of these models, making the process faster and more accessible.

**Applications:**
- **Education:** Enhances learning by providing realistic language practice and simulated real-world scenarios.

- **Entertainment:** Used to generate actors’ voices for dubbing, virtual assistants, or even create deepfake videos for parody or satire.

- **Accessibility:** Helps create personalized speech for those who have lost their voice due to illness (e.g., ALS patients).

- **Scams and Fraud:** Worryingly, AI-generated voice can be used in scams, such as impersonating family members in distress calls or mimicking executives to trick employees into financial transactions.

**Real-World Examples:**
- Scammers exploit cloned voices to create believable distress calls, convincing people to send money or reveal sensitive information.

- Media creators and companies use AI to re-create historical voices, or simulate live debates with political figures.

- Entertainers develop parody content using cloned voices of public figures, sometimes labeled as "ironic" to avoid legal repercussions.

**Legal and Ethical Implications:**
- **Legal:** The use of voice clones without consent raises significant intellectual property and privacy issues.

Some jurisdictions are considering or have introduced laws against unauthorized voice cloning.

- **Ethical:** There are growing concerns over consent, misuse, and the potential for deepfakes to erode trust in media and communication.

- The technology makes it harder to distinguish between real and fake audio/video, requiring new verification strategies (e.g., “safe words” for family, asking personal questions).

- High-quality voice cloning is costly at scale, but basic versions are inexpensive and accessible, increasing the risk of abuse.

- There is a pressing need for ethical guidelines and technical safeguards as these tools become mainstream.

**Challenges:**
- **Bias:** AI voice models can inherit biases from training data, impacting fairness and inclusivity, particularly in multilingual or dialectal use cases.

- **Job Displacement:** Automation of voice work may threaten livelihoods in areas like voice acting, call centers, and content creation.

Certainly!

**NUGGETS SUMMARY: VOICE CLONING & AI-GENERATED SPEECH TECHNOLOGY**

**1.

Title:

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.

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What is Voice Cloning Technology?

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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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.

**
- AI-powered voice cloning and text-to-speech (TTS) tools can now generate realistic, human-like voices in dozens of languages using minimal audio samples (sometimes as little as three seconds).

What is necessary for voice cloning to work?

- These systems analyze a speaker’s vocal patterns, timbre, accent, and intonation, then reproduce natural-sounding speech in multiple languages—sometimes making it possible for someone to “speak” a language they don’t know.

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

How will AI Voice help educators with building courses?

Title:

Content: Advertisement

An Advertising Company Wants to Make Deepfake Clones of Your Face

'[I]f all goes well it will be a viable way to make an income.'

A 3D illustration of a virtual face. iLexx / iStock

Do you need money? Of course you do.

If you can tolerate a degree of ambiguity and ethical gray zones, a startup will buy a digital deepfake copy of your face via which artificial intelligence software will sell people products and education services, according to a recent report from MIT Technology Review.

As of writing, the company has roughly 100 composite "faces" lined up. And it wants to add yours.

You don't need a model-tier face to sell it for deepfake advertising

"We've got a queue of people that are dying to become these characters," said Hour One's Strategy Lead Natalie Monbiot, in the report from MIT. To join the small army of brainless faces of the marketing world, deepfake hopefuls can apply on the company's website, where you can submit your Instagram profile, email address, and your (real) name. Naturally, model-tier faces aren't necessary, since Hour One wants to use a diverse repertoire of faces, of all ages, genders, and races. If you get picked, the firm will film your face speaking and contorting into a wide array of facial expressions with a green-screen background and a high-res camera. With footage in hand, the company will feed your likenesses into an AI system, which will build a composite character with which the company can sell whatever it wants.

As of writing, Hour One develops AI-generated voices to match each video, which isn't overwhelmingly different from text-to-speech software that enables AI to speak whatever you write. Presently, the startup says it's working with more than 40 clients, including firms from e-commerce, entertainment, real estate, and digital health. The AI startup can also offer client companies an elite package where it hires professional voice actors to stand in for your composite face, and read the sales script. One of Hour One's clients is Berlitz, a school for international language that generates teacher-led video courses on dozens of languages. Berlitz hired the company to increase the number of videos it can offer consumers, but it ran into a snag using human talent, since their production crews employed the same setup repeatedly, leading to a sense of stale redundancy. "They found it really unsustainable," noted Monbiot, in the MIT report. "A human being doesn't need to waste their time filming."

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AI deepfakes emulating human work with increasing fidelity

On the subject of profit margins alone, this is a win-win for all involved and a historic step in the application of AI software capabilities in the private sector. But like every new technology, it has a dark side. Obviously, the AI startup has an ethics policy, but the language describing character security is surprisingly loose, made up of only three bullet points and an ambiguous commitment to protect "your data assets with utmost security." For an added measure, the company will stamp every synthetic video of your digitized face with a watermark, affirming its artificial origin. But is it enough?

"This looks like a fairly extreme case of technology scaling back the human's role in a particular work process," said Jessie Hammerling of the Center for Labor Research and Education at the University of California, Berkeley, in the MIT report. This means that, while providing a perfect composite "middle-man" for human interaction on visual platforms and advertising, it's not only the security of the base-person's facial identity that could be at a higher risk, but also the prospect of humans who are used to the idea of building an in-person career in jobs that are emulated to increasing fidelity by nascent deepfake and other AI capabilities. And without recourse to an alternative or universal basic income, there may come a day when significant populations of real human beings have to search much harder to earn a living.

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Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

How is it Developed?

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:

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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.

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- Technological advances, such as those from ElevenLabs and Meta AI, often rely on large AI models trained with vast banks of spoken and written language data.

- To improve fidelity, data from both written and spoken resources are used, sometimes with paired sentences or crowd-sourced contributions.

- Continuous improvement is the norm; these systems adapt and enhance performance over time as more user data is integrated.

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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.

Web3 Page: 1 | 2 | 3

What is unique about Loora's AI English tutor?

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

Applications and Use Cases:**
- **Entertainment:** AI voice cloning creates alternate reality media (e.g., famous people speaking unfamiliar languages or performing songs they never recorded).

- **Accessibility:** Fast, consistent translation and dubbing open new possibilities for accessibility, such as AI-dubbed documentaries (China Media Group), AI language tutors (Loora), or real-time translation for spoken-only languages.

How will AI Voice help educators with building courses?

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

- **Marketing & Business:** AI-voiceover and video tools like Vidnoz AI allow rapid content localization, lip-syncing, and message customization across languages.

How will AI Voice help educators with building courses?

- **Education:** Language learning benefits from natural-sounding, customizable AI tutors that adapt to accent and topic.

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.

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

Enhance pronunciation abilities
Enhance language comprehension
Respond to different learning demands

- **Negative Uses (Scams):** The same fidelity used for positive applications enables deepfake scams—fraudulent calls or messages using cloned voices of family members or officials.

What are some risks regarding AI voice clning?

Title:

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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Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

Legal and Ethical Implications:**
- **Copyright and Consent:** Using someone’s likeness or voice may violate rights of publicity or copyright, especially if done without consent.

- **Fraud and Misinformation Risks:** The capacity for imitation makes phishing, impersonation, and disinformation campaigns more accessible and credible.

What are some risks regarding AI voice clning?

- **Data Security:** Training these models can raise concerns about how voice samples are obtained, stored, and protected.

- **Equity & Bias:** The technology may not equally represent all languages or dialects, possibly marginalizing underrepresented groups.

Title:

Content: Bridging Language Barriers: The Role of Global Voice and Speech Recognition in a Connected World

In an increasingly globalized world, the ability to communicate effectively across language barriers is becoming more critical than ever. With the advent of advanced technology, we are witnessing the rise of global voice and speech recognition systems that are playing a significant role in bridging these language gaps. These innovative tools are not only transforming the way we communicate but are also fostering greater understanding and collaboration among people from different linguistic backgrounds.

Global voice and speech recognition systems are computer-based technologies that convert spoken language into written text. They are capable of understanding and interpreting human speech, thereby allowing for real-time translation and transcription. This is particularly useful in a world where international communication is commonplace, and the need for quick and accurate translation is paramount.

These systems are being integrated into a wide range of applications, from smartphones and smart home devices to customer service and healthcare. For instance, multinational corporations use voice and speech recognition technology to provide customer support in multiple languages, enhancing their global reach and customer satisfaction. In the healthcare sector, these systems are used to transcribe medical records, thus improving efficiency and reducing the risk of errors.

Moreover, these technologies are playing a pivotal role in breaking down language barriers in education. They enable students to access learning materials in various languages, thereby promoting inclusivity and diversity. For non-native speakers, these tools can provide language learning support, making education more accessible and equitable.

The global voice and speech recognition market is growing at an unprecedented rate, reflecting the increasing demand for these technologies. According to a report by Grand View Research, the market is expected to reach USD 31.82 billion by 2025, growing at a compound annual growth rate (CAGR) of 17.2% from 2019 to 2025. This growth is driven by advancements in artificial intelligence and machine learning, which are making these systems more accurate and efficient.

However, despite the significant strides made in this field, there are still challenges to overcome. One of the main issues is the accuracy of translation. While these systems have improved considerably, they are not yet perfect and can sometimes misinterpret or mistranslate speech. This can lead to misunderstandings and miscommunications, which can be particularly problematic in sensitive situations such as diplomatic negotiations or legal proceedings.

Furthermore, these systems often struggle with understanding and translating less common languages or dialects. This can exclude certain communities from benefiting from these technologies, thus exacerbating existing language barriers.

Despite these challenges, the potential of global voice and speech recognition systems in bridging language barriers cannot be overstated. As these technologies continue to evolve and improve, they will undoubtedly play an increasingly important role in fostering global communication and understanding. They represent a significant step towards a world where language is no longer a barrier but a bridge connecting different cultures and communities.

By

What are some risks regarding AI voice clning?

- **Brand Consistency vs.

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

Manipulation:** While brands value consistency, tools could create unauthorized messages or content.

What are some risks regarding AI voice clning?

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

Real-World Examples:**
- AI-generated songs featuring famous voices not authorized by those artists have gone viral.

- Companies are raising funds for AI tutors that claim to rival real human engagement.

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.

- AI-dubbed documentaries and cross-lingual marketing empower global reach.

Title:

Content: Advertisment

China Media Group Debuts AI-dubbed English Documentary, Pioneering Global Communication

China Media Group launches its first AI-dubbed English documentary, enhancing global reach and fostering international understanding through advanced AI technology.

Aqsa Younas Rana
Updated On
New Update

In a groundbreaking move, China Media Group has launched its first AI-dubbed English documentary, marking a significant milestone in the use of artificial intelligence for global media outreach. This innovative approach to dubbing not only showcases the advancements in AI technology but also underscores China's ambitions to foster better international communication and understanding. Through this initiative, the documentary, originally produced in Mandarin, has been made accessible to a broader English-speaking audience, enhancing its global reach and impact.

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Revolutionizing Content Accessibility

The application of AI in dubbing the documentary into English reflects a growing trend in leveraging technology to bridge language barriers. Similar to the educational advancements discussed in 'Voice Cloning in Education: Bridging Language Gaps in Learning Environments,' this initiative by China Media Group capitalizes on the potential of AI voice cloning technology. By generating lifelike digital replicas of human voices, the documentary's AI-dubbed version maintains the authenticity of the original narration while making it understandable for English-speaking viewers. This technological leap not only improves accessibility but also ensures the delivery of content with emotional depth and cultural nuances intact.

The launch of this AI-dubbed documentary serves as a testament to China's commitment to enhancing global dialogue and cultural exchange. By removing language barriers, China Media Group is effectively broadening the documentary's audience, enabling people from different parts of the world to gain insights into Chinese culture, history, and perspectives. This initiative aligns with the broader objective of promoting mutual understanding and respect among diverse global communities, paving the way for more inclusive and informed international discourse.

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Setting New Standards in Media Production

China Media Group's pioneering use of AI technology in documentary dubbing sets new standards for media production and distribution. It illustrates the potential of AI to transform traditional media practices, making content more accessible and engaging for global audiences. As AI technology continues to evolve, it is likely to open up further possibilities for creating multilingual content, thereby enhancing the reach and impact of media across borders. This development also raises important considerations regarding the ethical use of voice cloning technology, underscoring the need for guidelines that ensure its responsible application in media and beyond.

As we reflect on the implications of this technological advancement, it becomes clear that AI-dubbed media content holds significant promise for fostering international understanding and cooperation. By making diverse cultural and educational materials available in multiple languages, we can build a more connected and informed world. The initiative by China Media Group not only highlights the practical applications of AI in media but also invites us to contemplate the future of global communication in an increasingly digital age.

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- Scams using cloned voices (e.g., fraudulent calls “from” family members) have already been reported.

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

Ongoing Challenges:**
- Technology is advancing rapidly—day by day, not year by year—so regulation and ethical frameworks must keep pace.

- The balance between innovation, creative use, and responsibility remains critical, especially where consent, authenticity, and impact on employment are concerned.

- Users, businesses, and educators are urged to stay informed, consider ethical ramifications, and advocate for responsible use alongside legal compliance.

**Conclusion:**
Voice cloning technology delivers powerful tools for communication, education, and content creation but also demands vigilance regarding privacy, consent, security, and authenticity.

Both its creative and deceptive potentials are growing as rapidly as the technology itself.

What are some risks regarding AI voice clning?

**Nuggets of Information from the Extract on AI and Voice Technology in Education & Beyond:**

- **AI in Course Creation:**
  - AI speeds up educational product/curriculum development – course structure generation can take minutes, with later human revision and expert review.

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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Go to

- AI can generate texts, suggest titles for courses or long-form materials, and assist throughout lesson design (tools such as ChatGPT, TurboText, Webcanape, and WebX).

- Quality control is crucial; over-reliance on AI may lead to a flood of low-quality, untested courses.

- **Voice and Audio AI Applications:**
  - Neural networks can now realistically synthesize natural human speech from text, allowing for “natural” sounding AI voices.

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

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

Difficult to distinguish from human voice

- Text-to-speech tools are highly accessible; users simply provide text and receive a realistically voiced audio output.

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

- Major companies (Google, Meta, Amazon, NVIDIA) invest heavily in speech recognition and synthesis, using advanced models optimized for efficiency on specialized hardware (like NVIDIA GPUs).

Title:

Content: OpenAI, a non-profit artificial intelligence developer, claims that its speech recognition software is highly efficient.
recommendations
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.
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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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Popular news

- **Medical and Accessibility Innovations:**
  - AI-driven brain-computer interfaces are enabling new methods of communication for individuals with severe disabilities (e.g., stroke patients can “speak” via AI-powered avatars that decode brain signals into 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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- Fewer phonemes are required for these systems to decode language, making communication more efficient for non-verbal individuals.

- **Audio Enhancement Technology:**
  - AI tools (e.g., Adobe Enhance Speech) significantly improve audio quality, removing noise and upgrading bad recordings to near-studio quality.

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."
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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

- Free and commercial solutions are available, with increasing accessibility to both educators and the public.

- **Voice Cloning:**
  - AI can mimic any individual’s voice, converting recorded texts into different voices, even allowing gender or accent changes (important for language learning simulation and accessibility).

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

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

What is necessary for voice cloning to work?

- OpenAI has developed advanced voice cloning models (Voice Engine) but currently limits public access due to deepfake concerns.

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

- **Risks and Ethical Dilemmas:**
  - Voice cloning and audio AI raise serious ethical issues: potential for deepfakes, identity theft, deception, and reputational harm.

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

- Developers remain cautious, balancing the innovation with risks (e.g.

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

OpenAI restricts their own technology’s release).

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.
Subscribe to our Telegram-channel t.me / sudua and to Google News SUD.UA, as well as to our VIBER, Facebook page and Instagram to be aware of the most important events.
The status of limited fit will be canceled: how it will affect the mobilization
The status of limited fit will be canceled: how it will affect the mobilization
The main thing about court
Today is Birthday Celebration
• Igor Zavalnyuk
Judge of the Odessa District Administrative Court
• Lyudmila Kosik
Judge of the Svyatoshinsky District Court of the City of Kyiv

- There is a larger debate about truthfulness, accuracy, and potential harm resulting from AI-generated content.

Title:

Content: Go to main content
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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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What are some risks regarding AI voice clning?

- **Legal Considerations:**
  - Use of AI for copying or simulating voices is under increasing scrutiny; unauthorized cloning (without consent) may breach privacy, intellectual property, or even criminal law.

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.

- Some uses (accessibility, language learning, entertainment) are encouraged, but the same technologies enable scams and misinformation.

What are some risks regarding AI voice clning?

**Summary:**
AI-powered voice generation and cloning technologies have revolutionized curriculum design, accessibility, entertainment, and medical communication.

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.

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

While educational applications are promising—enabling quick content creation and authentic voice material for learners—significant risks remain in the form of deepfakes, misuse, and insufficient oversight.

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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What are some risks regarding AI voice clning?

Continued ethical consideration, rigorous quality control, and legal safeguards are essential as such tools become more widespread and accessible.

**Voice Cloning Technology: Summary of Key Points**

**What is Voice Cloning Technology?

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. ”
More from the middle gate.
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Most preferred in this section.

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

important vocal nuances
intonation
timbre

**
- Voice cloning uses artificial intelligence (AI), particularly deep-learning algorithms, to create digital replicas of human voices.

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.
Related News
Using Artificial Intelligence to Implement the Most Dangerous Voice Fraud
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- With as little as 5–10 seconds of recorded speech, AI can generate highly realistic synthetic voices capable of reading any script as if spoken by the original person.

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

Difficult to distinguish from human voice

What is necessary for voice cloning to work?

**How is it Developed?

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

Deepdub, a film dubbing company, uses an AI to process voice and translate into a different language and promises to preserve what?

**
- AI models are trained on large datasets containing audio samples of the target voice.

What is necessary for voice cloning to work?

- Advanced techniques, such as transfer learning and deep neural networks, enable high accuracy, especially when ample training data is available.

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

- Specialized GPU hardware accelerates the training and deployment of these models, making the process faster and more accessible.

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

**Applications:**
- **Education:** Enhances learning by providing realistic language practice and simulated real-world scenarios.

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

- **Entertainment:** Used to generate actors’ voices for dubbing, virtual assistants, or even create deepfake videos for parody or satire.

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

- **Accessibility:** Helps create personalized speech for those who have lost their voice due to illness (e.g., ALS patients).

- **Scams and Fraud:** Worryingly, AI-generated voice can be used in scams, such as impersonating family members in distress calls or mimicking executives to trick employees into financial transactions.

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

could become a popular method of attacking banks and financial services

**Real-World Examples:**
- Scammers exploit cloned voices to create believable distress calls, convincing people to send money or reveal sensitive information.

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

- Media creators and companies use AI to re-create historical voices, or simulate live debates with political figures.

- Entertainers develop parody content using cloned voices of public figures, sometimes labeled as "ironic" to avoid legal repercussions.

**Legal and Ethical Implications:**
- **Legal:** The use of voice clones without consent raises significant intellectual property and privacy issues.

Some jurisdictions are considering or have introduced laws against unauthorized voice cloning.

- **Ethical:** There are growing concerns over consent, misuse, and the potential for deepfakes to erode trust in media and communication.

What are some risks regarding AI voice clning?

- The technology makes it harder to distinguish between real and fake audio/video, requiring new verification strategies (e.g., “safe words” for family, asking personal questions).

What are some risks regarding AI voice clning?

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

Difficult to distinguish from human voice

- High-quality voice cloning is costly at scale, but basic versions are inexpensive and accessible, increasing the risk of abuse.

- There is a pressing need for ethical guidelines and technical safeguards as these tools become mainstream.

**Challenges:**
- **Bias:** AI voice models can inherit biases from training data, impacting fairness and inclusivity, particularly in multilingual or dialectal use cases.

What are some risks regarding AI voice clning?

- **Job Displacement:** Automation of voice work may threaten livelihoods in areas like voice acting, call centers, and content creation.

Certainly!

Title:

Content: Grow with AppMaster.
Become our partner
How to use AI App Builder to create intelligent learning applications?
Intelligent learning applications powered by artificial intelligence (AI) technology have transformed the field of education by providing personalized and engaging learning experiences.
These applications employ advanced algorithms and machine learning to analyze student performance, identify knowledge gaps, and tailor content to meet individual learning needs.
AI-driven learning tools are being used in a variety of educational institutions, including K-12 schools, higher education institutions, and professional training organizations, providing seamless delivery of teaching materials, assessment, and engagement tools.
With the increasing popularity of e-learning and the continuous integration of artificial intelligence in education, intelligent learning application development has become a highly sought after field.
The Importance of Artificial Intelligence in Education
AI has the potential to revolutionize education, facilitate personalized learning, enhance data analytics, enable adaptive learning systems, and facilitate effective communication between educators and students.
Here are some of the ways in which AI plays a key role in modern education:
Personalized learning paths: AI-driven applications can analyze learner strengths, weaknesses, and preferences to create tailored learning plans that allow students to learn at their own pace and improve their understanding of complex topics.
• Automated assessments and feedback: AI can automatically rate assignments, quizzes, and other assessments, saving teachers time while providing immediate feedback to students.
This efficiency allows educators to focus on developing curricula and supporting students.
Data-driven insights: Through data analytics, AI can identify patterns in student performance and help educators understand and address students ’ specific needs, interests, and learning styles.
This information can enhance instructional design and provide targeted support to learners.
• Intelligent tutoring systems: AI-based tutoring systems can provide personalized feedback, tips, and support, allowing students to learn from their mistakes and deepen their understanding of concepts.
These systems can also adapt teaching methods to ensure the most effective learning experience.
Better communication and collaboration: AI-driven platforms can facilitate seamless communication between students and faculty, break down geographical barriers and provide diverse opportunities for collaboration and engagement.
Given the many benefits that AI brings to education, developing intelligent learning applications has the potential to have a significant impact on learners and educators around the world.
Choosing the Right AI Application Builder
Developing intelligent learning applications can be complex, but choosing the right AI application builder can make your task much easier.
There are several platforms that offer application building services, but not all are able to handle the complexities and requirements of AI-driven learning applications.
There are a few factors to consider when choosing an AI application builder:
Intuitive user interface: Application builders should provide a user-friendly interface to simplify the application development process.
Drag and drop features and other visual aids can make application layouts, workflows, and interaction designs more manageable for both technical and non-technical users.
• AI Integration: Ensure application builders support integrated AI technologies such as machine learning models, natural language processing (NLP), and computer vision.
This is essential for personalization, analytics, and automation in learning applications.
Scalability: As the user base of the application grows, so does its resource requirements.
Choose an application builder that allows you to deploy scalable applications that can handle increased data processing and user traffic without compromising performance.
• Data management and security: Your learning applications will handle sensitive student data, making data security a top priority.
Application builders should provide robust data management and security features to protect users ’ data from unauthorized access, corruption, and other threats.
Flexibility and customization: The best AI app builders provide design flexibility that allows you to create custom app features, workflows, and data structures to meet the unique requirements of your learning application.
Support for multiple platforms: Your learning app should be accessible on a variety of platforms, including web, Android, and iOS devices.
The AI application builder you choose should support cross-platform development and deployment, ensuring that your users have a seamless experience no matter which device they prefer.
Documentation and support: Comprehensive documentation, tutorials, and customer support can greatly improve your app building experience.
Choose a platform that offers ready-made guides and resources to help you effectively build and maintain intelligent learning applications.
By considering these factors and evaluating your application development needs, you can choose the right AI application builder platform to simplify and streamline the development process, enabling you to create superior intelligent learning applications.
How to Create Smart Learning Apps with AI App Builder
Creating a smart learning application with an AI application builder involves several steps to ensure that your application is efficient, user-friendly, and meets the needs of educators and learners.
Here are the main steps to follow:
1.
Define purpose and target audience: Determine the main purpose of the application, such as assisting with language learning, math, or exam preparation.
Identify your target audience by considering age groups, learner skill levels, and educational background.
2.
Choose the right AI application builder: Choose an AI application builder that supports building intelligent learning applications, has an easy-to-use interface, and offers AI-enabled features such as natural language processing and machine learning capabilities.
Consider a no-code platform like AppMaster, which simplifies application development.
3.
Create responsive and intuitive UI / UX designs: Design user interfaces for a variety of screen sizes and devices, such as smartphones, tablets, and web browsers.
Optimize UI / UX for ease of use and ensure smooth navigation, attractive visuals, and an engaging experience.
4.
Integrate AI-powered capabilities: Leverage AI technologies such as natural language processing, machine learning, and speech recognition to create personalized learning experiences, analyze user data, and deliver adaptive content based on learner performance and preferences.
5.
Build back-end infrastructure: Develop back-end systems that support scalable server architectures, secure data storage, and seamless communication between application components.
Visualize the development backend via the drag-and-drop interface using the AppMasterno-code platform.
6.
Integration of third-party tools and APIs: Enhance application functionality by integrating external tools such as payment gateways, chatbots, and analytics services.
Use the AppMaster API to simplify integration and ensure smooth interoperability between application components and external services.
7.
Test and optimize applications: Thoroughly test and optimize application performance, availability, and reliability.
Identify performance bottlenecks, fix bugs, and enhance user experience through iterative testing and optimization.
8.
Publish and Deploy: After testing and finalizing an app, publish it to an app store such as Google PlayApp Store or deploy it as a web app.
Release applications with minimal effort using AppMaster ’ s seamless deployment capabilities.
9.
Monitoring and Updates: Continuously monitor user feedback and usage metrics to identify areas for improvement, update according to user needs, and roll out new features to keep users engaged and enhance the learning experience.
AppMaster: Comprehensive No-Code Tool for AI Application Development
As a powerful no-code application creation tool, AppMaster simplifies the process of developing AI-driven intelligent learning applications.
With AppMaster, you can design backend, web, and mobile applications intuitively with an intuitive drag-and-drop interface.
AppMaster also offers a wide range of customization options that enable developers to create unique and engaging learning experiences without having to write a single line of code.
Some of the key benefits of using AppMaster for AI application development include:
Visual Backend, Web, and Mobile Application Development: AppMaster ’ s visual design environment automates complex tasks through a simple drag-and-drop interface, eliminating manual coding and accelerating application development.
• Customizable Business Processes and APIs: AppMaster enables you to design custom business processes with its powerful Business Process Designer and build a wide range of APIs for seamless integration with external tools and services.
Secure and Scalable Infrastructure: Build applications using a robust back-end architecture to ensure security, scalability, and high performance.
With AppMaster, you can deploy applications to the cloud or host them locally using source files or binaries.
• Efficient collaboration and rapid development: AppMaster simplifies collaborative application development, enabling teams to collaborate efficiently and quickly test their applications with auto-generated applications and open API documentation.
With its wide range of features and capabilities, AppMaster enables professional and citizen developers to easily create scalable and engaging AI-driven intelligent learning applications.
Key Features Included in Smart Learning Applications
To create a successful AI-driven intelligent learning application, consider including the following key features:
Personalized content: Utilizing AI algorithms to analyze user data and behavior, enabling applications to deliver customized learning experiences and content based on individual learner preferences and performance.
• Adaptive Learning Path: Integrate AI-driven adaptive learning systems that automatically adjust learning cadence and content based on learner progress and understanding to ensure the best learning experience for each user.
• Analysis and Reporting: Provides detailed analysis and reporting tools to help educators and learners gain insight into performance, progress, and areas for improvement.
Combined with machine learning, continuous improvement and adaptation based on user data.
Gamification elements: Incorporate gamification elements such as rewards, badges, and leaderboards to motivate users and increase engagement while learning.
Leverage artificial intelligence and machine learning to provide personalized feedback and suggestions for improvement.
• Chatbots and voice assistants: Integrate AI chatbots and voice assistants that support natural language processing to help learners answer questions, provide explanations, and provide personalized learning support.
• AR / VR capabilities: Use augmented reality (AR) and virtual reality (VR) technologies to create immersive, interactive learning experiences that allow students to visualize complex concepts and interact innovatively with learning materials.
Collaboration tools: Seamless communication and collaboration between educators, learners, and peers through integrated messaging systems, forums, and project management tools.
• Security and privacy: Implement robust security measures and data protection practices to protect user data and privacy and ensure a safe and trusted learning environment.
By integrating these capabilities and leveraging the power of AI app builders like AppMaster, you can create a compelling, user-centric intelligent learning app that revolutionizes the way students learn and engage with educational content.
Examples of AI Driven Intelligent Learning Applications
There are a number of well-known AI learning applications that have had a significant impact on the education industry.
These applications demonstrate how AI can enhance a student ’ s learning experience by providing personalized content, adaptive learning paths, and sophisticated analytics.
Here are some examples:
1.
Duolingo: Duolingo is a language learning platform that offers personalized courses to help learners develop language skills effectively and efficiently.
It uses AI-driven algorithms to customize lesson plans, measure learners ’ abilities, and adjust content based on users ’ progress.
Its intelligent chatbot function can simulate conversations with native speakers, helping learners practice and improve conversation skills.
2.
Brainly: Brainly is an online learning platform where millions of students collaborate and help each other answer questions related to various subjects.
AI algorithms analyze questions from students, match them to relevant topics, and connect them to students or experts who can provide the most appropriate solution.
This AI-driven approach makes Brainly a popular and reliable resource for academic support.
3.
Quizlet: Quizlet is a learning platform designed to help students prepare for exams by offering interactive learning sets, practice quizzes, and learning games.
It uses AI to analyze each user ’ s learning patterns, curate personalized content, and implement adaptive learning systems to improve learner engagement and performance.
4.
Socratic by Google: Socratic is an AI-driven educational app that provides students with guidance and support in specific disciplines.
It uses advanced AI models to analyze complex problems, identify basic concepts, and plot steps to interpret resources and solve problems.
Socratic ’ s intelligent search capabilities make it a valuable tool for students seeking clarification on a variety of topics.
5.
Thinkster Math: Thinkster Math is an iPad app that combines AI-driven technology and human expertise to provide students with personalized math tutoring.
The app ’ s artificial intelligence algorithms assess how students learn and progress, and tailor the curriculum accordingly.
It also provides in-depth analysis and feedback, enabling parents and tutors to monitor students ’ improvement and understanding of mathematical concepts.
These AI-driven learning applications exemplify the potential of AI in enabling personalized and efficient education.
By harnessing the power of AI, educators and developers can create a new generation of innovative learning solutions.
Final thoughts
Creating intelligent learning applications using AI application building tools such as AppMaster can revolutionize the education industry by providing personalized, engaging, and effective learning experiences.
As we have seen, AI-driven learning applications enable customized content delivery, adaptive learning systems, advanced data analytics, and enhanced communication between educators and students.
AppMaster ’ s comprehensive no-code platform simplifies the development of AI-driven learning applications, providing visual design capabilities for back-end, web and mobile applications in addition to drag-and-drop tools and customizable business processes.
These capabilities enable developers to focus on integrating the advanced AI capabilities needed to create truly intelligent learning applications, transforming the way students learn and interact with educational content.
Take the first step in designing intelligent learning applications by exploring AppMaster ’ s powerful no-code platform and contributing to shaping the future of education.
Can AppMaster be used to create intelligent learning applications with AI capabilities?
AppMaster is a versatile no-code platform that enables educators and instructional designers to create intelligent learning applications without the need for extensive coding skills.
It offers a range of AI-driven components and capabilities, making it a valuable tool for developing interactive and personalized learning experiences.
How can AI app developers enhance the learning experience?
AI application developers can analyze individual students ’ learning patterns and adjust content to suit their progress and preferences.
This leads to a more engaging and effective learning experience.
Can AI app builders be used in formal educational settings, such as schools and universities?
Yes, AI app builders are valuable tools for educational institutions.
They can be used for classroom learning or e-learning platforms and are suitable for a variety of educational environments.
What is an AI app builder and how does it relate to intelligent learning apps?
An artificial intelligence application builder is a tool that utilizes artificial intelligence to simplify the application creation process.
When applied in the field of education, these builders can develop intelligent learning applications that deliver personalized, interactive, and adaptive learning experiences.
What are the main features of the AI Application Builder used to create intelligent learning applications?
Features may include natural language processing, machine learning, personalized content delivery, analytics that track student progress, and the ability to create interactive quizzes, games, or simulations.
Are AI app builders suitable for all types of learning applications?
AI application builders are versatile and can be used for all types of learning applications, from language learning to math and science education.
They excel in scenarios where personalized learning is essential.
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