Voice cloning technology is a type of artificial intelligence that can clone voices in multiple languages, with some tools needing only a three-second voice sample to generate a cloned voice.

This technology has the potential to enhance language comprehension and pronunciation abilities, and can be used to create personalized audiobooks and educational videos.

However, it also raises concerns about copyright violation and abuse, highlighting the need for guidelines and regulations.

The development of voice cloning technology began in late 2022, with private testing conducted with trusted partners, and companies like OpenAI have been cautious in its release due to the potential for synthetic speech abuse.

One of the significant risks associated with voice cloning is its potential for fraud and scams, where AI-generated voice calls can be used for impersonation, leading to financial or personal harm.

To mitigate these risks, OpenAI has implemented measures such as digital watermarking to track the source of audio generated by its Voice Engine, and advocates for voice authentication to verify consent.

Moreover, the company suggests maintaining a "no-go voice list" to prevent the impersonation of specific individuals without their consent.

The use of voice cloning technology in education can also promote inclusivity, as it can help non-native speakers access learning materials and break down language barriers.

Additionally, voice cloning technology can provide personalized learning experiences, which can be particularly beneficial for students with disabilities or language barriers.

However, there are also potential drawbacks to using voice cloning technology in educational settings, such as the risk of bias and the potential for students to rely too heavily on technology.

To mitigate these risks, educators can use voice cloning technology in conjunction with traditional teaching methods, and ensure that students are critically evaluating the information they are receiving.

The integration of voice cloning technology into educational settings raises considerations for responsible and ethical use, including respecting creators' rights and reducing language barriers.

It is essential to prioritize cultural sensitivity and respect in generated content, and to review output for pronunciation and intonation accuracy.

The global voice and speech recognition market is growing rapidly, with the market expected to reach USD 31.82 billion by 2025, but accuracy of translation is a significant challenge for these systems.

Overall, the integration of voice cloning technology into educational settings has the potential to improve accessibility and language learning outcomes, but it requires careful consideration of technical requirements, cultural nuances, and ethical implications.

The development and use of voice cloning technology also raise important ethical considerations, such as the potential for abuse, fraud, and social resilience.

To address these concerns, it is essential to develop and implement robust regulations and guidelines for the use of voice cloning technology, ensuring that it is used responsibly and for the benefit of society.

Ultimately, the effective use of voice cloning technology in foreign language instruction requires a deep understanding of its potential applications, limitations, and ethical implications, as well as a commitment to responsible innovation and development.

The use of voice cloning technology in language learning can improve teaching and learning efficiency, quickly identifying students who need speaking practice.

AI voice over generators can translate text to speech in 24 languages, adjusting tone, pace, and accent, and considering cultural nuances.

These generators can be used in e-learning platforms for multilingual courses, but data privacy is an important consideration.

To critically distinguish between real and cloned voices, students need to be aware of the potential for abuse and be skeptical of audio that seems too good to be true.

Experts suggest adding security steps to prevent deepfake scams, such as being aware of the risks and taking steps to verify the authenticity of audio.

The development and use of voice cloning technology raises ethical challenges, such as the potential for misidentification and the need for regulation.

The Microsoft VALL-E system can mimic a person's voice from a 3-second sample, and it can convert written texts into audio clips with matching tone and style.

VALL-E can simulate room acoustics and sound effects with high accuracy, and it can create audio clips with custom reading style and tone of voice.

For generating realistic and engaging Listening Comprehension materials for foreign language instruction at low proficiency levels, suitable voice cloning models and algorithms include ElevenLabs, Voicebox, Listnr AI, NeuralSpace VoiceAI, and BigSpeak AI.

These models can be used to create personalized and interactive learning materials, but it is essential to consider the ethical challenges and legal implications of using voice cloning technology in education.

The use of voice cloning technology in foreign language instruction raises concerns about data privacy, cultural sensitivity, and the potential for misuse, highlighting the need for careful evaluation and responsible implementation.

Overall, voice cloning technology has the potential to revolutionize the way we interact with audio content, and educators can leverage this technology to create personalized learning materials for students with different needs and proficiency levels.

However, the use of voice cloning technology also raises important ethical and legal concerns that need to be addressed, such as the potential for scams, fraud, and social resilience.

To address these concerns, it is essential to develop and implement robust regulations and guidelines for the use of voice cloning technology, ensuring that it is used responsibly and for the benefit of society.

Ultimately, the effective use of voice cloning technology in foreign language instruction requires a deep understanding of its potential applications, limitations, and ethical implications, as well as a commitment to responsible innovation and development.

Voice cloning technology is a type of artificial intelligence that can clone voices in multiple languages, with some tools needing only a three-second voice sample to generate a cloned voice.

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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What is necessary for voice cloning to work?

This technology has the potential to enhance language comprehension and pronunciation abilities, and can be used to create personalized audiobooks and educational videos.

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

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

Enhance language comprehension
Enhance pronunciation abilities

However, it also raises concerns about copyright violation and abuse, highlighting the need for guidelines and regulations.

The development of voice cloning technology began in late 2022, with private testing conducted with trusted partners, and companies like OpenAI have been cautious in its release due to the potential for synthetic speech abuse.

Title:

Content: OpenAI, the creators of ChatGPT, provided a glimpse into their latest artificial intelligence (AI) innovation on Friday—a tool known as Voice Engine, capable of generating “natural-sounding speech” and mimicking human voices with remarkable accuracy. According to OpenAI’s blog post, Voice Engine can produce lifelike speech from just a single 15-second audio sample, closely resembling the original speaker.

This cutting-edge AI tool has far-reaching applications, including reading assistance, content translation, and providing a voice for individuals who are nonverbal or afflicted by speech conditions. Despite its potential benefits, OpenAI acknowledges the serious risks associated with Voice Engine, particularly in an election year.

Development of Voice Engine began in late 2022, with private testing conducted among a select group of trusted partners starting late last year. OpenAI stresses that these partners adhere to stringent usage policies, ensuring explicit consent from the original speaker and prohibiting unauthorized impersonation.

To maintain transparency, any audio generated by Voice Engine is watermarked to aid in tracing its origin. OpenAI advocates for widespread deployment of voice authentication to verify the original speaker’s consent and suggests implementing a “no-go voice list” to prevent the creation of voices resembling prominent figures.

Moreover, OpenAI recommends phasing out voice-based authentication for sensitive information access, such as bank accounts. Despite these precautions, the company remains cautious about releasing Voice Engine more broadly.

OpenAI aims to foster a dialogue on the responsible deployment of synthetic voices, considering societal adaptation to these advancements. Based on ongoing discussions and test results, the company will make informed decisions regarding the technology’s widespread deployment.

The unveiling of Voice Engine comes amid escalating concerns surrounding AI-generated deepfakes and their potential to propagate misinformation, particularly in the context of elections. As OpenAI navigates the ethical and societal implications of Voice Engine, the tech community awaits further insights into the future of this transformative AI tool.

By Impact Lab

What are some risks regarding AI voice clning?

One of the significant risks associated with voice cloning is its potential for fraud and scams, where AI-generated voice calls can be used for impersonation, leading to financial or personal harm.

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OpenAI Reveals New Voice Replication Tool Will Be Strictly Regulated to Prevent Abuse
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U.S. artificial intelligence (AI) development company OpenAI today revealed a voice copying tool that intends to implement strict controls before implementing protection against speech fraud.
According to an OpenAI blog post sharing the results of the small scale test, the model, called Voice Engine, can mainly copy a person ’ s voice based on a 15-second sound sample.
San Francisco-based OpenAI said, “We acknowledge the significant risks involved in generating speech that resembles someone ’ s voice, especially given the election year … We work with U.S. and international partners in government, media, entertainment, education, civil society, and other areas to ensure that we incorporate their input into the build process. ”
Fake information researchers are concerned that AI-powered applications are being abused in a critical election year, as voice copying tools become more and more affordable, easy to use, and difficult to track.
OpenAI, which recognises these issues, said it would be cautious and kept abreast of wider releases "based on the potential for synthetic speech abuse."
A few months ago, a political adviser to a Democratic presidential primary candidate in the United States admitted to impersonating President Joe Biden ’ s voice by calling AI-generated automated voice calls that sounded like Biden ’ s call to voters not to vote in January ’ s New Hampshire primary.
The incident alarmed experts who feared a flood of AI-generated fake information ahead of the US presidential election in November and other important elections around the world.
OpenAI said that partners testing the Voice Engine have agreed to a number of specifications, including requiring that all voices copied by the tool be given explicit and informed consent.
OpenAI also said that it is also necessary to clearly inform the audience that the sound they hear is generated by AI.
“We have implemented a range of security measures, including digital watermarking to track the source of all audio generated by the Voice Engine and proactively monitor how the tool is used, ” OpenAI said.
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What do cybersecurity experts believe about the use of synthesized voice?

could become a popular method of attacking banks and financial services

To mitigate these risks, OpenAI has implemented measures such as digital watermarking to track the source of audio generated by its Voice Engine, and advocates for voice authentication to verify consent.

Moreover, the company suggests maintaining a "no-go voice list" to prevent the impersonation of specific individuals without their consent.

The use of voice cloning technology in education can also promote inclusivity, as it can help non-native speakers access learning materials and break down language barriers.

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.

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How will AI Voice help educators with building courses?

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

Additionally, voice cloning technology can provide personalized learning experiences, which can be particularly beneficial for students with disabilities or language barriers.

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

Respond to different learning demands
Enhance language comprehension

However, there are also potential drawbacks to using voice cloning technology in educational settings, such as the risk of bias and the potential for students to rely too heavily on technology.

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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

What are some risks regarding AI voice clning?

To mitigate these risks, educators can use voice cloning technology in conjunction with traditional teaching methods, and ensure that students are critically evaluating the information they are receiving.

What are some risks regarding AI voice clning?

The integration of voice cloning technology into educational settings raises considerations for responsible and ethical use, including respecting creators' rights and reducing language barriers.

How will AI Voice help educators with building courses?

It is essential to prioritize cultural sensitivity and respect in generated content, and to review output for pronunciation and intonation accuracy.

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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

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

The global voice and speech recognition market is growing rapidly, with the market expected to reach USD 31.82 billion by 2025, but accuracy of translation is a significant challenge for these systems.

Overall, the integration of voice cloning technology into educational settings has the potential to improve accessibility and language learning outcomes, but it requires careful consideration of technical requirements, cultural nuances, and ethical implications.

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

The development and use of voice cloning technology also raise important ethical considerations, such as the potential for abuse, fraud, and social resilience.

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Speech cloning raises concerns, OpenAI again explains its text-to-speech tool
2024 / 6 / 10 9: 57: 21 Source: IT House Author: Yuanyang Editor: Yuanyang
OpenAI explained its text-to-speech tool for the second time in a few months, and again stressed that the tool is not currently widely available and may not be available in the future.
“Whether or not we end up deploying this technology at scale, it ’ s important for people around the world to understand where it ’ s going, ” OpenAI said in a statement on its website Friday.“ That ’ s why we want to explain how the model works, how we use it for research and education, and how we implement security measures around the technology. ”
At the end of last year, OpenAI shared its “voice engine ” with a small number of external users.
The engine uses text input and a 15-second clip of human voices to “generate a natural sounding human voice that is very similar to the original speaker. ”
The tool could create fake, multilingual human voices, and the company said at the time that it had chosen to preview the technology rather than launch it at scale to “enhance social resilience ” to the threat posed by“ increasingly realistic artificial intelligence-generated models. ”
As part of these efforts, OpenAI says it is actively phasing out ways to use voice recognition for bank account verification, exploring policies to protect individual voices for use in AI, educating the public about the risks of AI, and accelerating the development of technologies to track audiovisual content so users can identify whether they are interacting with real people or synthetic content.
However, despite these efforts, concerns about the technology remain.
Bruce Reed, the head of artificial intelligence for US President Joe Biden, has said that voice cloning is one of the reasons he can't sleep at night.
The Federal Trade Commission said in March that scammers were using AI technology to increase the credibility of their fraud, using voice cloning tools that make it harder for people to distinguish between AI-generated voices and human voices.
“We continue to engage with U.S. and international partners from government, media, entertainment, education, civil society, and more to ensure we incorporate their feedback in the build process, ” the company also noted, once the“ Voice Engine ” is equipped with its latest model, GPT-4o, it will also bring new threats.
The company says it is actively “conducting ‘ red team testing ’ on GPT-4o to identify and address known and unknown risks from areas such as social psychology, bias and fairness, and misinformation. ”
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To address these concerns, it is essential to develop and implement robust regulations and guidelines for the use of voice cloning technology, ensuring that it is used responsibly and for the benefit of society.

Title:

Content: You can copy your voice in 15 seconds!
OpenAI Announces New Voice Engine Tool
▲ This technology is at risk of abuse. OpenAI is only available to partners at this stage and is not yet open to the public. (Graph / CFP)
Journalist Chan Ya-ting / General Report
American artificial intelligence development company OpenAI on Friday (29) revealed that the voice AI tool "Voice Engine", just 15 seconds of speaking sound samples, can copy the voice of the person, and the result is not limited by the sound sample language. If you speak English, this technology can use your voice to generate results in Spanish, French and other languages.
However, due to the risk of abuse, OpenAI is only available to partners at this stage and is not yet available to the public.
The New York Times and the Associated Press reported that OpenAI entered the field of speech technology, sharing test results after applying for the trademark Voice Engine, but considering the possibility of synthetic speech abuse, especially worried that the technology could be used to destroy voice authenticators such as online bank accounts, OpenAI is now taking a cautious attitude towards wider release.
OpenAI pointed out that there are significant risks in producing voice-like speech, especially in an election year when Voice Engine testing partners have agreed to regulations such as disclosing to audiences that sound is generated by AI and that the original voice must have explicit and informed consent.
In addition, OpenAI said that the company has implemented a number of security measures, including the use of digital watermarks to track the source of all the audio generated by the Voice Engine and actively monitor its usage.
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Ultimately, the effective use of voice cloning technology in foreign language instruction requires a deep understanding of its potential applications, limitations, and ethical implications, as well as a commitment to responsible innovation and development.

The use of voice cloning technology in language learning can improve teaching and learning efficiency, quickly identifying students who need speaking practice.

Title:

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

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

Respond to different learning demands
Enhance language comprehension
Enhance pronunciation abilities

What is unique about Loora's AI English tutor?

AI voice over generators can translate text to speech in 24 languages, adjusting tone, pace, and accent, and considering cultural nuances.

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

How will AI Voice help educators with building courses?

These generators can be used in e-learning platforms for multilingual courses, but data privacy is an important consideration.

How will AI Voice help educators with building courses?

To critically distinguish between real and cloned voices, students need to be aware of the potential for abuse and be skeptical of audio that seems too good to be true.

Title:

Content: Aug 31, 2022

Now, software can replicate your boss’s voice and tell you what to do

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"Deepfake" audio technology is here, and scammers are taking advantage.

If you’re listening to or have already listened to the beginning of this episode, you probably noticed that the voice introducing Kimberly Adams sounded a bit off, right?

That’s because it’s an audio “deepfake,” and it was created by Yisroel Mirsky at the Offensive AI Research Lab through a process called voice cloning.

It uses software to study a short sample of someone’s voice and create a deepfake, which in this case took only 15 seconds to generate, according to Mirsky.

It’s far from a perfect replica, but it turns out that scammers recently started to use deepfake audio for telephone scams and in some cases have succeeded.

Marketplace’s Kimberly Adams recently spoke with Kyle Alspach, a cybersecurity reporter with Protocol, about how the tech behind audio deepfakes works and how they’re being used in phone scams. The following is an edited transcript of their conversation.

Kyle Alspach: The technology involves having [artificial intelligence], deep learning, and it takes an audio sample of someone’s voice. It can be as little as three seconds, and it trains itself on the way that this person sounds. And it creates a model that can then be used to replicate that person’s voice. The current way that it works is you have to use text to speech, which is just you type in a phrase, and then it speaks using the cloned voice.

Kimberly Adams: How are these audio deepfakes being used in scams?

Alspach: So they’re, at least we know, being used to target businesses at this point, especially larger businesses. Someone will call up pretending to be someone else with someone else’s voice, typically some kind of executive or someone’s boss, and ask them to transfer funds or ask them for password credentials, that kind of thing. And in some cases, they have been successful.

Adams: Do you have a sense of how common audio deepfakes are now? And where do experts in the industry see it going?

Alspach: You know, among the larger businesses, I think more and more of them are starting to see these because they’re really ripe targets for this kind of thing. But right now, I don’t think that it’s something that a lot of people are seeing, but it is the beginning of this kind of technology being used in this way.

Adams: What do cybersecurity experts suggest that regular people or businesses do to avoid falling for these deepfake audio scams?

Alspach: For business purposes, for instance, if you’re going to transfer money, you might want to add some additional steps to that process and involve someone saying some kind of challenge phrase or something like that, that everyone’s agreed on beforehand, [to] prevent that from happening. But the biggest thing is just to be aware that it might happen to you and to pay attention when someone calls you up and make sure that it actually sounds the way you would expect, and they are asking you for things that they normally would be asking you for. It’s really at this point kind of a low-tech approach to defending against this kind of thing. But really, it’s just creating the possibility in your mind of this happening. And I guess, unfortunately, you kind of have to become more skeptical now when people call you up.

You can read more of Alspach’s reporting on audio deepfakes here.

Yisroel Mirsky told us that the tech he used to generate the deepfake audio for Alspach’s article, and for our show, is “relatively old.”

Alspach also mentioned in his piece that there is an open-source voice cloning tool online that anyone — even scammers can download and potentially use.

But as we found out, getting that software to work isn’t a simple process of downloading and hitting the Install button.

Tech barriers can stop you at a number of steps in the process. Like, if you don’t know the coding language Python or if your computer isn’t powerful enough, you’ll likely be unable to use it, as our producer Daniel Shin discovered.

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Every day, the “Marketplace Tech” team demystifies the digital economy with stories that explore more than just Big Tech. We’re committed to covering topics that matter to you and the world around us, diving deep into how technology intersects with climate change, inequity, and disinformation.

As part of a nonprofit newsroom, we’re counting on listeners like you to keep this public service paywall-free and available to all.

Support “Marketplace Tech” in any amount today and become a partner in our mission.

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What are some risks regarding AI voice clning?

Experts suggest adding security steps to prevent deepfake scams, such as being aware of the risks and taking steps to verify the authenticity of audio.

What are some risks regarding AI voice clning?

The development and use of voice cloning technology raises ethical challenges, such as the potential for misidentification and the need for regulation.

Title:

Content: Politics 2023-08-24T20: 32: 22 + 03: 00
Ukrainian News
“This is not my voice, ” Tishchenko said about the fake information attack
“This is not my voice, ” Tishchenko said about the fake information attack
HELP UKRAINIAN NEWS
Nikolay Tishchenko.
Photo: Suspіlne
Recordings of telephone conversations in which a man with a voice similar to the voice of the People ’ s Deputy from the Servant of the People party Nikolai Tishchenko openly demands millions of dollars for his own protection for illegal call centers have been replicated by the country ’ s leading media and telegram channels with millions of audiences, writes Delo.ua.
The MP himself reacted as follows: “This is not my voice and there have never been such negotiations. ”
Also Tishchenko added that similar to his voice in audio recordings was generated by a neural network, and fraud in call centers are engaged in technically savvy young people who know how to use neural networks.
It should be noted that the technology of voice reproduction, which would be very difficult to distinguish from the voice of a real person, do exist.
For example, this was achieved by researchers from Microsoft.
But this is one of the most recent developments, so the code of the new model of artificial intelligence Vall-E they carefully hide and declare that AI is not available to the public and is used only for research purposes.
In addition, the developers claim that there is always an opportunity to check whether the voice is real.
"Because VALL-E can synthesize language that preserves the identity of the speaker, this could carry potential risks in misusing the model, such as faking voice identification or impersonating a particular speaker.
To reduce such risks, you can build a detection model to distinguish whether an audio clip has been synthesized by VALL-E.
We will also apply the principles of Microsoft AI in practice in the further development of models, ” – said the developers of Microsoft.
Thus, while neural models are not able to transmit emotions in the voice, make pauses, simulate "moaning", or characteristic for people sounds between phrases, such as a long "e" or "a", which can be evidence of the authenticity of posted on the Internet audio recordings of a person with a voice similar to the voice of Deputy Mykola Tishchenko.
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The Microsoft VALL-E system can mimic a person's voice from a 3-second sample, and it can convert written texts into audio clips with matching tone and style.

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Content: Chairman of the Board of Directors and Editors
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Mohamad Elbaz
Editor-in-Chief
Wael Lotfy
Chairman of the Board of Directors and Editors
I'm sorry.
Mohamad Elbaz
Editor-in-Chief
Wael Lotfy
Microsoft has developed a language system that can mimic a person ’ s voice from a sample of just three seconds.
Microsoft has developed an intelligent language system, an AI-powered program that can mimic someone ’ s voice and mimic their voice from a three-second audio sample.
The new system, called VALL-E, converts written texts into audio clips, and speech can match both the speaker ’ s tone of voice and the way of talking — even room acoustics, where it can be used for custom or sophisticated text-to-speech applications.
Not only does the system create audio clips by writing random texts, but it can also take into account the reading style and tone of voice, to show the character of the original voice in the fake audio clips.
The system is still under development and research, but the project offers a high level of accuracy in simulating the factors and sound effects surrounding the speaker in the original clip of only 3 seconds, so that they are highlighted in the manufactured clips closer to the truth.
Samples of audio clips presented by "Microsoft" to reveal the capabilities of its new system, a precise level of the program in creating audio clips as recorded during a phone call, by quoting the style of sound and its level and intensity, from the original clip recorded to the user during his speech in fact.
And proved "Microsoft" through the audio clips published on the page of the new system on "JetHub" that the system can create audio clips in different ways, using the voice of one person.

What is necessary for voice cloning to work?

VALL-E can simulate room acoustics and sound effects with high accuracy, and it can create audio clips with custom reading style and tone of voice.

For generating realistic and engaging Listening Comprehension materials for foreign language instruction at low proficiency levels, suitable voice cloning models and algorithms include ElevenLabs, Voicebox, Listnr AI, NeuralSpace VoiceAI, and BigSpeak AI.

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

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Text to Speech AI Tool ElevenLabs Completes Testing Stage, Supports 28 Languages including Chinese
2023 / 8 / 24 12: 16: 10 Source: IT House Author: Yuanyang Editor: Yuanyang
ElevenLabs, an AI text-to-speech company, recently announced the expansion of its platform to launch a new text-to-speech model “Eleven Multilingual v2 ” that supports 28 languages and automatically recognizes 28 languages and converts text to speech.
The expansion marks the formal completion of the testing phase of the platform, making it available for businesses and individuals.
The platform uses a new self-developed AI model that can automatically recognize multiple languages, including Chinese, and generate speech with “rich emotions. ”
Users can use the platform ’ s sound cloning tool to speak in nearly 30 languages without having to enter text.
Mati Staniszewski, CEO and co-founder of ElevenLabs, said in a statement: “ElevenLabs ’ dream is to make all content available in any language and in any voice.
With this release, we are one step closer to realizing this dream, enabling all dialects to have human-level AI voices.
Our text-to-speech generation tools help all creators get high-quality voice content. ”
But ElevenLabs has yet to address another contentious issue surrounding its platform and others like it: the threat to the dubbing industry.
A little over a month ago, ElevenLabs closed a $19 million Series A round led by entrepreneurs Nat Friedman and Daniel Gross and a16z (Andreessen Horowitz), valuing the company at close to $100 million.
Languages now supported by Elevenlabs include:
Chinese, Korean, Dutch, Turkish, Swedish, Indonesian, Tagalog, Japanese, Ukrainian, Greek, Czech, Finnish, Romanian, Danish, Bulgarian, Malay, Slovak, Croatian, Advanced Arabic and Tamil.
English, Polish, German, Spanish, French, Italian, Hindi and Portuguese were and are supported.
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Content: Meta Announces Voicebox Model That Will Revolutionize Text-to-Speech
Meta announced on Friday what it said was a revolution in speech generative artificial intelligence, as competition with other tech giants such as Google, Microsoft and Amazon escalated.
In a blog post, Meta said she has developed Voicebox, a modern AI model that can perform speech creation tasks such as editing, sampling, and style, and is specially trained to do so by learning in context.
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The tech giant, which owns Facebook, Instagram, WhatsApp and others, said that VoiceBox can produce high-quality audio clips and edit previously recorded audio, such as: removing car horns, or barking dogs, all while maintaining the content and tone of voice.
Voice Box is also multilingual and can produce speech in six languages.
Meta believes that in the future, multipurpose AI models such as VoiceBox can give natural sounds to virtual assistants and non-player characters in Metaphors.
The company said that these models can allow visually impaired people to hear written messages from friends read by artificial intelligence with their voices, give creators new tools to create audio clips for videos and edit easily, and much more.
Using a two-second audio sample, VoiceBox can match the sound pattern and use it to create text-to-speech technology.
Meta said the new multipurpose AI model could recreate a piece of speech interrupted by noise, or replace words uttered wrongly without having to re-record the entire speech.
When giving a sample of someone ’ s speech and a passage of text in English, French, German, Spanish, Polish, or Portuguese, the VoiceBox model can read the text in any of those languages, even when the speech and text model are different languages.
Meta hopes that in the future this possibility will be used to help people communicate in a natural and real way even if they do not speak the same languages.
Thanks to learning from the diverse data, the company said its model could generate more representative speech for how people speak in the real world and in the six languages it currently supports.
Meta sees VoiceBox as an important step forward in her research into generative artificial intelligence, and she looks forward to continuing her exploration of the acoustic space and seeing how other researchers rely on her work.
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Content: Listnr AI
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Get a better experience using the Listnr AI desktop app on WebCatalog Desktop for Mac, Windows and Linux.
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Listnr is an online text-to-speech tool developed by Listnr Inc.
It transforms text into lifelike speech using advanced AI sounds.
Key features include: * 900 + sounds in 142 languages * Natural voice comments that look human * Customizable voice with pitch, speed, pauses, etc. * Download MP3 and WAV files * Embedded audio player * Podcast hosting * APIs for developers * Free and paid plans Listnr uses the latest AI technology to create human-looking voice comments from text: * Upload a text file or type / Paste text * Choose one of over 900 AI sounds * Preview and customize pitch, speed, etc. * Download realistic voiceover in MP3 or WAV format * Embed audio player or podcast hosting * Share your audio content anywhere * Advanced neural networks mimic human audio patterns to create incredibly natural audio results.
Website: listnr.ai
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Content: There were 107 press releases posted in the last 24 hours and 446,378 in the last 365 days.
VoiceAI, technology for local dialects, transforming global customer service experiences
NeuralSpace launches AI voices in local languages
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NeuralSpace's VoiceAI platform
LONDON, UNITED KINGDOM, December 10, 2023 / EINPresswire.com / --
NeuralSpace, a leader in linguistic artificial intelligence, has launched a transformative voice technology feature within its VoiceAI platform, offering realistic artificial sounds in Arabic, Hindi and English.
The innovation, unveiled on December 11, marks a major development in sound technology, offering speech formulation with unparalleled precision, especially in local dialects such as Saudi Arabia.
Three main advantages characterize NeuralSpace ’ s offerings:
Cultural Interaction: Artificial sounds capture the essence of local dialects, fostering deep communication between users and technology in regions such as Saudi Arabia, India and the English-speaking world.
Instantaneous Interaction: VoiceAI technology provides instantaneous, natural-sounding voice feedback, which is essential for dynamic speech generation in virtual assistants and voice response systems.
Ease of integration: The technology is sophisticated but easy to use, allowing developers to effortlessly optimize their applications.
VoiceAI for NeuralSpace meets the growing demand for accurate transcription, speech analytics and authentic synthetic sounds.
These AI sounds are finely tuned to real-world interactions, providing engaging and realistic user experiences.
Felix Le Mans, CEO and co-founder of NeuralSpace, said:
“NeuralSpace was founded with a vision to make the technology globally available in any language.
Today, with the release of our natural AI sounds, we are one step closer to turning this dream into reality.
Our human-quality Saudi, Indian and English voices in AI are not just revolutionizing technological innovation; they are gateways to make dialectical interactions with technology a tangible experience for everyone. ”
About VoiceAI: This platform and application programming interface (API) allow companies to copy, translate and analyze voice data with exceptional accuracy, especially in Arabic and Hindi.
Key features include up to 91% copy accuracy for these languages, surpassing major tech brands.
The platform also ensures high-level data security through in-house deployment, NeuralSpace ’ s ISO 27001 certification and compliance with the General Data Protection Law.
NeuralSpace invites you to integrate VoiceAI into your systems, and promises to change customer experiences.
The platform can be accessed via a code-free web platform, REST APIs, and Python SDK, ensuring easy integration.
About NeuralSpace: At the forefront of linguistic artificial intelligence, NeuralSpace is committed to technologies that enhance human-machine communication.
VoiceAI embodies this vision, reflecting the diversity and richness of human languages.
For more information, demos or enquiries, visit www.neuralspace.ai or contact sales @ neuralspace.ai.
NeuralSpace ’ s latest innovation is more than just a technological advance; it ’ s a step towards a future where you not only understand technology but also speak with a voice that resonates with the cultural richness of human languages.
Melanie Swamy-Brown
NeuralSpace
melanie @ neuralspace.ai
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Content: BigSpeak AI
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BigSpeak is a feature-rich text-to-speech and speech-to-text software that can be accessed online.
BigSpeak ’ s main features include converting written text to high-quality, realistic audio in a variety of languages.
It uses advanced machine learning algorithms to generate synthetic speech and supports translation in multiple languages to help overcome language barriers.
The speech-to-text feature also enables users to convert spoken to written text, making it easy to create transcripts based on audio input.
In addition, BigSpeak offers a “voice clone ” feature that allows users to create speech that mimics a specific sound or speech pattern to achieve a unique audio output.
An additional “text-to-video ” function is also implemented, which can produce videos generated by artificial intelligence based on the user ’ s text input.
BigSpeak ensures a high level of data security, with all processed data encrypted and securely stored in the cloud.
Enhanced editing options enable users to save time and effort by editing existing results instead of restarting the process.
A progress tracker is used to monitor and review work history.
BigSpeak ’ s services can be used for a wide range of applications, including creating audiobooks, generating sounds for different scenes, and more.
Website: bigspeak.ai
Disclaimer: WebCatalog does not have any affiliation, association, authorization, endorsement relationship with BigSpeak AI, nor is it formally associated in any way.
All product names, logos and brands are the property of their respective owners.
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How will educational institutions benefit from developing AI voice audio content for languages learners?

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

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

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

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

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

These models can be used to create personalized and interactive learning materials, but it is essential to consider the ethical challenges and legal implications of using voice cloning technology in education.

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AI voice pioneer ElevenLabs raises $80 million
ElevenLabs broke new ground in the voice AI industry, successfully raising an impressive $80 million in a Series B round led by industry giants such as Andreessen Horowitz, former GitHub CEO Nat Friedman, and renowned entrepreneur Daniel Gross.
The company has received investments from well-known companies such as Sequoia CapitalSmash CapitalSV AngelBroadLight CapitalCredo Ventures, which has raised a total of $101 million, giving it a valuation of more than $1 billion, exponentially growing and entering the Unicorn Alliance.
The previous year it was about $100 million.
CEO Mati Staniszewski laid out an ambitious fund-raising agenda, outlining aggressive product development, infrastructure expansion, team development, AI research, and plans to implement robust security measures to ensure ethical AI development.
In a letter to TechCrunch, Staniszewski said: “Our vision with this new investment is to consolidate ElevenLabs ’ leading position in global voice AI, both in pioneering research and in practical applications. ”
ElevenLabs, the brainchild of Piotr Dabkowski, a former Google machine learning engineer, and Staniszewski, a former Palantir strategist, was born out of a shared vision to improve speech cloning capabilities, fuelled by the two men ’ s experience shooting shoddy films in their respective home countries. Poland.
Since launching the beta a year ago, the company has quickly become known for its browser-based app, which cleverly synthesizes sounds and can be fine-tuned for tone, emotion and rhythm, and other sound nuances.
ElevenLabs offers a free and premium service that allows users to enter text for sound interpretation or submit speech samples for personalized speech cloning.
The company ’ s commitment to innovation extends to creating specialized voice generation for industries such as audiobooks, movie dubbing, game characters and promotions.
One of their breakthrough developments, launched last year, is the “speech-to-speech ” tool, which aims to retain the unique characteristics of the speaker ’ s voice while eliminating unwanted background noise and subtly tweaking the voiceover of film and TV content.
Going forward, ElevenLabs is about to launch an advanced voiceover studio workflow and mobile app designed to narrate web pages and text through its proprietary voice technology.
The company ’ s innovations have attracted a diverse customer base, including game developer Paradox Interactive and prominent media outlet The Washington Post.
Staniszewski proudly tells us that ElevenLab users have been generating audio content for more than a century, and now it ’ s a favorite tool for 41% of Fortune 500 employees.
The boom in AI-driven voice technology is paralleled by the iterative growth of AppMasterno-code platforms, which democratize application development for a variety of users.
As ElevenLabs continues to rise in the ranks of innovative technology companies, its trajectory gives us a glimpse of the transformative potential of AI in voice and speech.
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The use of voice cloning technology in foreign language instruction raises concerns about data privacy, cultural sensitivity, and the potential for misuse, highlighting the need for careful evaluation and responsible implementation.

Overall, voice cloning technology has the potential to revolutionize the way we interact with audio content, and educators can leverage this technology to create personalized learning materials for students with different needs and proficiency levels.

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

Respond to different learning demands
Enhance language comprehension

However, the use of voice cloning technology also raises important ethical and legal concerns that need to be addressed, such as the potential for scams, fraud, and social resilience.

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

could become a popular method of attacking banks and financial services