Voice cloning is an artificial intelligence technique that generates lifelike digital replicas of human voices by training on recordings of a target speaker and modeling distinctive features such as pitch, speed, and cadence. [1].

Many early systems required large, clean datasets, and because many algorithms were trained on English or Classical Arabic, applying them to other dialects can cause data drift that often requires retraining from scratch.

Modern approaches can clone a voice from very short samples, with Microsoft’s VALL-E producing speech that matches tone and speaking style from a 3‑second recording.

OpenAI’s Voice Engine can mimic a voice from a 15‑second sample and has been privately tested with partners since late 2022 for use cases including reading assistance and translation.

ElevenLabs supports multilingual cloning from a 3‑second sample and has been used to recreate the voices of deceased celebrities such as Judy Garland for audiobooks. [30].

Meta’s Voicebox generates speech in six languages and can edit pre‑recorded audio while preserving content and tone, indicating rapid advances in controllable speech synthesis. [38].

Additional systems include NVIDIA’s RAD‑TTS for controlled speech synthesis and voice transformation and OpenVoice V2 for fine‑grained style control and multilingual speech generation. [52].

Training custom models typically demands substantial compute and data engineering, with example requirements including multi‑core CPUs, 32 GB RAM, CUDA‑enabled NVIDIA GPUs, and GPU‑accelerated frameworks such as TensorFlow.

High‑quality bespoke cloning can be costly, with some services reported at up to $20,000 per minute.

In entertainment, voice cloning is used to simulate historical figures, create satirical content, localize films, and produce audiobooks, with platforms like Deepdub preserving timbre, rhythm, and intonation while reducing dubbing time and cost. [9][40].

Accessibility use cases include reading assistance, translation, and generating audio in familiar voices for blind or visually impaired users. [2][10].

Education and e‑learning leverage AI voices for multilingual courses, digital marketing and YouTube content, and conversational practice, with platforms such as Loora using AI‑driven voice interactions to improve English skills. [13].

Enterprise adoption is growing rapidly, with ElevenLabs reporting usage by employees at 41% of Fortune 500 companies.

The same realism fuels misuse, as fraudsters can clone voices from clips as short as 3 to 20 seconds to impersonate family members or public figures. [5][20].

The FTC warns that AI voice clones can turbocharge fraud, and fake kidnapping calls have used cloned voices to convincingly imitate loved ones.

Regulators are responding, including US actions banning AI‑generated voice calls and FCC rulings applying the TCPA to AI‑generated voices, which require prior express written consent for robocalls. [16].

Detection and defense tools are emerging, including Pindrop’s winning solution in the FTC Voice Cloning Challenge, Veridas Voice Shield making judgments from 3‑second samples, AI Detect’s classifiers, DeFake’s watermarking proposal, and Truecaller’s real‑time AI Call Scanner. [21].

Voice cloning raises complex legal questions about consent, ownership, and copyright, with concerns that platforms can appropriate unique artist voices without compensation and with unresolved voice rights in music and film. [11].

High‑profile disputes highlight these issues, including Scarlett Johansson’s allegations over unauthorized vocal resemblance and broader celebrity deepfake deceptions.

Companies may face liability for chatbot and AI system outputs, and traditional legal frameworks do not fully address accountability for generative systems.

OpenAI requires explicit consent for Voice Engine, watermarks generated audio for origin tracing, and recommends phasing out voice‑based authentication for sensitive access.

Policy experts urge regulations to manage deep counterfeiting and voice copying, define legal versus illegal uses, and ensure enforceable compliance.

Ethical risks include privacy invasion, manipulation via deepfakes, lack of informed consent, cultural insensitivity, and the exploitation of voices of deceased individuals. [14][10].

Researchers and startups warn of potential harm, calling for responsible development, technical transparency, and robust safeguards to minimize misuse. [6][12].

In education settings, UNESCO calls for clear guardrails for generative AI in schools, including data privacy protections, age limits, ethical validation, and transparency whenever AI‑generated content is used.

A notable real‑world example is the revival of Judy Garland’s voice for audiobook narration using ElevenLabs’ cloning technology.

Amazon Alexa can mimic voices from under a minute of recorded audio, raising questions about informed consent and ownership when reproducing voices of deceased family members or friends.

Scammers have targeted elderly people with cloned voices, and authorities in the UAE have warned about fraud schemes that derive voice models from social media audio. [20].

OpenAI’s Voice Engine pilots for reading assistance and translation illustrate beneficial applications alongside the company’s acknowledgement of serious risks.

For language instruction, AI voice‑over generators can produce multilingual materials with adjustable tone, pace, accent, and cultural nuance, improving accessibility for low‑proficiency learners when used carefully.

Educators should navigate copyright, privacy, and consent constraints, review platform terms, and implement strong data protection and transparency practices when deploying synthetic voices in coursework. [30][32][34][59].

Overall, voice cloning is rapidly becoming realistic and accessible, offering significant benefits in entertainment, accessibility, and education while requiring strong legal, ethical, and technical safeguards to mitigate scams, deepfakes, and rights violations. [6][7].

Voice cloning is an artificial intelligence technique that generates lifelike digital replicas of human voices by training on recordings of a target speaker and modeling distinctive features such as pitch, speed, and cadence. [1].

Title:

Content: General Supervision
Elham Aboul Fath
Editor-in-Chief
Thank you for your patience.
General Supervision
Elham Aboul Fath
Editor-in-Chief
Thank you for your patience.
A new invention in artificial intelligence imitates sounds
Some of the biggest players in AI are seeking to stay ahead of the competition by launching their own gadgets, with Meta recently introducing Voicebox, an artificial speech generator integrated with artificial intelligence and based on texts.
The company believes that thanks to this technology, it has surpassed all current models in the field.
And while the system isn ’ t widely available for public use yet, Meta has made demos available to anyone interested in learning more about Voicebox.
The system can be used to edit acoustics through a natural sound generator, and can intelligently edit noise in audio files and reproduce sound accurately.
Voicebox is able to match the style of voice input and generate audio text clips, allowing blind users to provide the system with an audio clip of one of their friends so Voicebox can read their messages written in their friend ’ s voice using artificial intelligence.
The system can solve tasks through contextual learning, so that it can process texts that have not been given before and generate context and changes in the same way that people read by relying on previous knowledge to learn and face new challenges.
The ethical and legal implications of this new tool cannot be ignored, as anyone can produce audio clips using someone ’ s audio recordings and claiming to speak anything they want, without permission.
The company claims in its paper that the binary classification model can distinguish between real speech and that it was created by Voicebox.
Voicebox trains over 60,000 hours of English audiobooks and 50,000 hours of multilingual audiobooks in six different languages.
The system can also convert written text into spoken speech in one or several languages without having to be specially trained for each language.
Meta claims that Voicebox can produce various audio clips 20 times faster than Microsoft ’ s Val-E and with better quality.
In addition to high speed and accuracy, Voicebox can generate audio clips in different languages without having to be specially trained for each language.

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

What is necessary for voice cloning to work?

Many early systems required large, clean datasets, and because many algorithms were trained on English or Classical Arabic, applying them to other dialects can cause data drift that often requires retraining from scratch.

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

Modern approaches can clone a voice from very short samples, with Microsoft’s VALL-E producing speech that matches tone and speaking style from a 3‑second recording.

Title:

Content: Chairman of the Board of Directors and Editors
I'm sorry.
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?

OpenAI’s Voice Engine can mimic a voice from a 15‑second sample and has been privately tested with partners since late 2022 for use cases including reading assistance and translation.

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 is necessary for voice cloning to work?

ElevenLabs supports multilingual cloning from a 3‑second sample and has been used to recreate the voices of deceased celebrities such as Judy Garland for audiobooks. [30].

Title:

Content: Sunday 07 July 2024
Chairman of the Board of Directors and Editors
Abdurrahim Ali
Editor-in-Chief
Dalia Abdul Rahim
Chairman of the Board of Directors and Editorial Board
Abdurrahim Ali
Editor-in-Chief
Dalia Abdul Rahim
Gate Light
Artificial intelligence tool narrates audiobooks with the voices of deceased actors
Follow the latest news through the app
Fans of classic films are now able to revive the voices of their late stars thanks to a new and controversial technology.
The British company Eleven Labs, launched by two Polish entrepreneurs, announced the development of an artificial intelligence tool capable of cloning the voices of late movie stars to be used to record audiobooks, articles and electronic documents.
Scary technique.
The new technique is based on the use of "generative" artificial intelligence models that are trained using real voice recordings of actors.
These models are able to analyze the acoustic patterns and recognize the subtleties that characterize the sounds of these stars, and then use this data to produce new recordings that are accurate and realistic.
Reviving the voice of Judy Garland
Judy Garland, best known for her timeless performance of "Somewhere Over the Rainbow" in the 1939 film The Wizard of Oz, was one of the first names to use the technique to revive her voice.
Lisa Minnelli, daughter of Judy Garland, expressed her delight at the move, noting that “it ’ s exciting to see our mother ’ s voice available to countless millions of people who love her. ”
Collaborating with celebrity heirs
The British company not only limited itself to Judy Garland, but also reached deals with the heirs of Sir Laurence Olivier, James Dean, and Burt Reynolds.
These deals allow fans of these stars to listen to audiobooks, novels and articles recorded with their voices.
Controversy and fears
Besides the enthusiasm aroused by this technique, there are also many concerns.
Last year, Hollywood saw a 118-day strike by actors who feared movie studios would replace them with technology.
These concerns are not unfounded, as the technology clearly demonstrates the ability of artificial intelligence to imitate human voices with astonishing realism.
Other uses of artificial intelligence in music
The initiative is part of a wider wave of artificial intelligence in the music and entertainment industry.
For example, Paul McCartney and film director Peter Jackson used an AI tool to isolate John Lennon's voice from an old recording, allowing them to finish "The Beatles' Last Song."
The live performances also saw the use of holographic technology to revive the performances of Michael Jackson and rapper Tupac.
Continuous development
Eleven Labs, founded by Matty Staniszowski and former Google engineer Piotr Dabkowski, has been a huge success and has raised millions of pounds, raising its value to more than $1 billion (£783 million).
The company also offers a wide range of other synthetic sounds, such as “middle-aged American male ” and“ optimistic millennials. ”
A controversial future.
As for the future of this technology, the question remains: will it still be a way to revive the legacy of late artists or will it spark further debate about the impact of technology on art and creativity?
It seems that artificial intelligence will continue to advance, which will allow us to rethink the concept of originality and creativity in the digital age.

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

What company created an AI tool that could mimic the voices of deceased movie stars?

What is necessary for voice cloning to work?

Meta’s Voicebox generates speech in six languages and can edit pre‑recorded audio while preserving content and tone, indicating rapid advances in controllable speech synthesis. [38].

Title:

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.
You are here because you are interested in technical news.
Subscribe to our newsletter
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.
This site uses cookies to enhance your experience and your visit to our site ok More

Additional systems include NVIDIA’s RAD‑TTS for controlled speech synthesis and voice transformation and OpenVoice V2 for fine‑grained style control and multilingual speech generation. [52].

Title:

Content: Home > Industry > Keyword > Robotics News > Text
AI Daily: The domestic robot Astribot S1 is coming; Synthesia pushes digital people who can read text emotions; OpenVoice V2 version is released; DeepFacelive lets you change faces in real time during live streaming
2024-04-26 15: 19 · Source: Webmaster 's House
Welcome to the "AI Daily" column! Here is your guide to exploring the world of artificial intelligence every day. Every day, we show you the hot content in the AI field, focus on developers, and help you understand the technology trends and understand the application of innovative AI products.
Fresh AI products click https: / / top.aibase.com /
Synthesia launches a new digital person Expressive-1 official version to understand the emotions in your text
Synthesia introduced Expressive-1AI Avatars, an AI virtual image technology that automatically displays rich expressions based on text content.
The technology improves video expressiveness and attractiveness, with enhanced expressiveness, synchronization of emotional responses, and mimicking human microexpressions and body language.
【 AiBase Summary: 】
• Enhanced expressiveness: Expressive-1 automatically displays adaptive intonation, facial expressions, and body language based on text semantic changes to express emotions more naturally.
Synchronization of emotional responses: Virtual images can accurately display expressions and intonations that match emotional states, improving the accuracy of emotional expression.
Sound and lip syncing: Each virtual image is equipped with a matching sound and excellent lip syncing technology to ensure consistent voice and lip movements.
Details Link: https: / / top.aibase.com / tool / synthesia
2, the news fly star fire big model V3.5 upgrade to launch long text, long picture text, long speech big model
Xunfei released Xunfei Spark large model V3.5 upgrade, the introduction of multi-emotion superanthropomorphic technology, the introduction of long text, long picture text, long speech large model, and Spark intelligent body platform to provide strong technical support for bidding applications and contract applications.
【 AiBase Summary: 】
University of Science and Technology announced the upgrade of the Star Fire Model V3.5, introducing the multi-emotion superanthropomorphic synthesis technology.
Launched the first long text, long text, long speech model to provide more powerful technical support.
The Spark model excels in general-purpose long text processing, even surpassing the GPT-4Turbo.
Details Link: https: / / top.aibase.com / tool / xunfeixinghuorenzhidamoxing
3, HKUST News Fly: News Fly Star Fire V4.0 version released on June 27
Xunfei released the first large model that supports long text, long text and long voice, providing a series of new functions, including image recognition, contract assistant, intelligent bid evaluation assistant, etc., to achieve more vivid and personalized expression, solve the problem of enterprise landing, and help employees improve their work efficiency.
【 AiBase Summary: 】
The first large model supporting long text, long picture text and long voice, providing more professional and accurate industry scene answers.
Introduced contract assistant and intelligent bid evaluation assistant to improve the efficiency of contract audit and make bid evaluation more convenient, efficient and accurate.
Launched a new intelligent body platform to solve the problem of large model enterprises landing, create exclusive assistants for employees, and help enterprises to liberate productivity.
Details Link: https: / / top.aibase.com / tool / xunfeixinghuorenzhidamoxing
4, the domestic robot will come!
Astribot S1
Astribot S1, a domestic AI robot that subverts the field of housework robots, has core features such as imitation learning, large model blessing, software and hardware collaboration.
Its excellent operational performance, demonstrating multi-tasking capabilities in home and work scenarios, heralding the potential for widespread use of AI robots in future life.
【 AiBase Summary: 】
Imitation Learning: Astribot S1 imitates human behavior and performs complex tasks, demonstrating agility and flexibility in adults.
The big model blessing: access to the big model test, expected to be commercialized in 2024, aims to establish a new AI robot standard.
Hardware and software collaboration: The R & D team made a key breakthrough, enabling the S1 to have a smart “brain ” and an agile“ body ”.
5, the foot of the big man seconds to become cute Lori!
DeepFacelive allows you to change your face in a second in the live broadcast
DeepFacelive is a widely watched tool that can change faces in real time during live and video calls, bringing users a whole new visual experience.
The introduction of this technology improves accuracy and authenticity, adding interesting and innovative space.
【 AiBase Summary ： 】
You can change faces in real time during video calls and live broadcasts, and you can change facial expressions and images in real time.
⊙ Including face animator, can operate static face pictures
Hardware and system requirements: RTX2070 and above graphics card, win10 system, 4GB RAM, 32GB + page file
Project address: https: / / top.aibase.com / tool / deepfacelive
OpenVoice V2 release allows fine control of sound style
OpenVoice V2 is an innovative sound cloning technology that accurately replicates the voice of the reference speaker and generates speech in multiple languages.
This version has better audio quality and native multilingual support, integrates MeloTTS technology and supports free commercial use.
Technical methods include decoupling design of sound styles and languages, basic pronunciator TTS models and timbre converters, and training strategies and data processing.
【 AiBase Summary: 】
Accurate Tone Cloning: OpenVoice can accurately clone reference tones and generate speech in multiple languages.
Flexible sound style control: Users can adjust the mood, accent, rhythm, pause and tone of the sound in detail to achieve personalized sound output.
Efficient compute performance: OpenVoice maintains high performance while significantly reducing compute costs.
Website: https: / / research.myshell.ai / open-voice
Project address: https: / / top.aibase.com / tool / openvoice
Create your own voice bot: https: / / myshell.ai /
Intel's first quarter results were strong
Intel ’ s revenue in the first quarter reached $12.7 billion, up 9% year-on-year, driven mainly by computing, artificial intelligence and edge products.
Intel has launched a new Gaudi3AI accelerator, challenging rivals Nvidia and AMD to make progress in the field of artificial intelligence.
Intel is accelerating the launch of AI PC products, which is expected to exceed 40 million AI PC shipments by the end of 2024.
【 AiBase Summary: 】
Intel ’ s first quarter revenue reached $12.7 billion, up 9% year over year.
Intel launches new Gaudi3AI accelerator, challenging rivals Nvidia and AMD to make progress in artificial intelligence.
Intel is accelerating the launch of AI PC products, which is expected to exceed 40 million AI PC shipments by the end of 2024.
Technology giant engineers pay secret: OpenAI engineers make $900,000 a year
At tech giants, engineers earn millions of dollars a year, of which OpenAI engineers earn up to $900,000 a year.
The salary levels of engineers vary from company to company, but they are all in the millions of dollars. Once promoted to senior positions, engineers can earn millions of dollars a year.
Talents in the field of artificial intelligence are generously rewarded for their knowledge.
【 AiBase Summary: 】
OpenAI engineers earn up to $900,000 a year
  Google, Apple, Facebook, Microsoft and other companies engineer salaries are more than $1 million
⊙  Engineers can earn millions of dollars a year after promotion to senior positions
9, IntrinsicAnything: adjust the image light to keep the object material
This article introduces a method to standardize the optimization process by generating model learning materials to improve the accuracy of restoring object material in pose images taken under unknown static lighting conditions.
Through the model basis of diffuse reflection and specular reflection coloring items, the researchers used the training strategy from coarse to fine to achieve stable and accurate material recovery results.
【 AiBase Summary: 】
✔ Generate model learning materials, standardize the optimization process, improve accuracy
➢ Models based on diffuse and specular coloring items for increased accuracy
Using a rough to fine training strategy to achieve stable and accurate material recovery results
Details Link: https: / / top.aibase.com / tool / intrinsicanything
Align Your Steps: Low Step Reasoning to Maintain High Quality Results
This article introduces a new method called Align Your Steps, which aims to optimize the sampling schedule of diffusion models (DMs) in the field of deep learning and improve the efficiency and quality of the generation process.
Through rigorous quantitative experiments, it is found that the optimization program significantly improves image quality in image generation benchmark, and is applicable to the field of text-to-image and video generation.
【 AiBase Summary: 】
Optimize sampling plan to improve the efficiency and quality of the generated model
Can be used for a variety of data synthesis benchmarks, including images, videos, etc.
Provides user-friendly plug-and-play optimization planning applications to improve stability and quality during the build process
Details Link: https: / / top.aibase.com / tool / align-your-steps
11, the new ID to keep the project PuLID: image background, light, style, etc., all maintain a high degree of consistency
PuLID is an emerging ID retention project that aims to improve ID retention and minimize the impact on the original model.
Its core strengths include high consistency, versatility, high fidelity, stability and accuracy, and a wide range of applications. The release of PuLID will drive innovation and development of the technology, demonstrating unique advantages and value.
Let us look forward to the release of PuLID and witness its brilliant performance in the field of technology.
【 AiBase Summary: 】
High consistency: Before and after the identity information is added, the background, lighting, layout and style of the image are consistent.
Multi-Functionality: Support a variety of operations such as style change, IP fusion, accessory modification, attribute editing and ID mixing to show powerful functions and effects.
✔ High fidelity: By contrast alignment, custom IDs remain high fidelity, providing users with more possibilities and choices.
Details Link: https: / / top.aibase.com / tool / pulid
Physical Education Teacher Using Artificial Intelligence to Clone Headmaster ’ s Voice in Retaliation Arrested
This article reports on the incident in Baltimore County, Maryland, where physical education teacher Damien Darion used an artificial intelligence speech cloning service to frame the principal of Parksville High School.
The incident revealed the risk of AI technology being misused and raised concerns about personal information security and privacy protection.
【 AiBase Summary: 】
Artificial intelligence cloning of the principal ’ s voice: PE teacher Darien was arrested on suspicion of making false recordings.
Risk Warning: Abuse of AI voice cloning technology raises social concerns, and OpenAI restricts public use of its platform.
Privacy Protection: Lawmakers work to enact laws to protect personal information from unauthorized use by tech companies.
Report it.
• Related recommendations
• Everyone is watching
Words everyone is searching for today:

What technology is able to replicate the voice of a speaker in multiple languages?

Training custom models typically demands substantial compute and data engineering, with example requirements including multi‑core CPUs, 32 GB RAM, CUDA‑enabled NVIDIA GPUs, and GPU‑accelerated frameworks such as TensorFlow.

Title:

Content: Grow with AppMaster.
Become our partner

How to Build Custom ChatGPT with OpenAI's GPT Builder

ChatGPT, derived from OpenAI's powerful GPT (Generative Pretrained Transformer) family, is a state-of-the-art conversational AI model capable of providing human-like responses to various questions and tasks. It has been extensively used in various applications, such as chatbots, customer support systems, and content generation, with its primary purpose being to engage in natural language interactions with users. With its remarkable performance in generating realistic and relevant text-based responses, ChatGPT has become an integral part of many modern AI systems.

To build a custom ChatGPT that caters to your specific project requirements, fine-tune the pre-trained model on a dataset that suits your domain of interest. This permits the model to learn the nuances of the target domain and generate responses that align more closely with your desired conversational AI experience.

Overview of OpenAI's GPT Builder

OpenAI's GPT Builder is a tool that allows you to create your own customized ChatGPT instances with a focus on your application's unique needs. By leveraging the powerful GPT model, GPT Builder helps you fine-tune the original model on a dataset of your choice, yielding optimized conversational AI experiences specifically tailored to your project.

GPT Builder streamlines the customizing ChatGPT models by providing an easy-to-use framework for dataset handling, model training, evaluation, and deployment. It allows you to experiment with configurations and perform necessary adjustments to achieve the desired output or balance model performance and resource constraints.

Image Source: The Verge

Setting Up the Development Environment

Before building your custom ChatGPT, it's crucial to set up a proper development environment. It will require specific hardware and software configurations to be in place:

Hardware Requirements

  • A powerful computer with a multi-core processor and sufficient amount of RAM (32 GB minimum).
  • An NVIDIA GPU with CUDA support and at least 12 GB VRAM for efficient model training and fine-tuning. Working with larger models may require more powerful GPUs or even multi-GPU setups.

Software Requirements

Install the following software components on your system:

  • Python 3.7 or above. Make sure to install the appropriate version for your operating system.
  • An installation of the TensorFlow library (version 2.x) with GPU support. TensorFlow is a popular open-source machine learning library that provides a comprehensive ecosystem for working with GPT-based models.
  • OpenAI library. This Python package allows you to access and utilize OpenAI's GPT models and APIs conveniently and straightforwardly.
  • Other required Python libraries, such as Numpy, Pandas, and requests, that are necessary for data manipulation, processing, and API calls.

Once your development environment is set up, you can start building your custom ChatGPT instance using OpenAI's GPT Builder. In the upcoming sections, we'll walk you through the steps required to select and prepare the dataset, build and fine-tune the model, test and evaluate its performance, and deploy it for practical applications.

Selecting and Preparing the Dataset

The success of your custom ChatGPT model heavily depends on the quality and diversity of the dataset used during the fine-tuning process. By selecting the right dataset, you can create a model that caters to your specific requirements and delivers the desired level of performance. Below are the steps to help you select and prepare the dataset for training your custom ChatGPT model.

Choose the Right Conversational Dataset

The first step is identifying a suitable conversational dataset that aligns with your project goals. There are several options when it comes to selecting the dataset:

  • Pre-existing datasets: You can train your model using publicly available conversational datasets like the Cornell Movie Dialogs Corpus, Persona-Chat dataset, or Stanford Question Answering Dataset (SQuAD).
  • Custom datasets: Alternatively, you can create a custom dataset that matches your domain or use-case. Consider collecting conversations from customer support chat logs, interviews, or any other context that fits your model's purpose. While creating such datasets, ensure the data is anonymized and properly consented to avoid privacy and ethical concerns.
  • Combination of datasets: You can also combine standard and custom datasets to create a richer and more diverse set of conversations for training your model.
Try AppMaster no-code today!
Platform can build any web, mobile or backend application 10x faster and 3x cheaper
Start Free

Clean and Preprocess the Dataset

Before feeding the dataset into your custom ChatGPT model, it is vital to clean and preprocess the data. This process has several steps, including:

  • Removing irrelevant content or noises such as advertisements or special characters.
  • Correcting grammatical and spelling errors, which might confuse the model during training.
  • Converting texts to lowercase to maintain uniformity.
  • Tokenizing your dataset, converting it into a format understandable by the model (e.g., splitting sentences into words or subwords).

Format the Training Data

After cleaning and preprocessing, you need to format your dataset according to OpenAI's GPT Builder’s requirements. Typically, chat-based models require a conversation to be formatted as a sequence of alternating user statements and model responses. Each statement and response pair should be clearly labeled, and special tokens should be used to indicate the beginning and end of a sentence or conversation. For example, if your dataset contains a conversation between a user (U) and a model (M), you can format it like this: ``` { "dialog": [ {"role": "user, {"role": "assistant, {"role": "user, {"role": "assistant ] } ```

By selecting the right dataset, cleaning and preprocessing it, and formatting it according to the model's requirements, you can create a strong foundation for building a powerful and accurate custom ChatGPT model.

Building and Fine-Tuning Your Custom Model

Once you have prepared your dataset, the next step is to build and fine-tune your custom ChatGPT using OpenAI's GPT Builder. The following steps outline the process of model building and fine-tuning:

Initialize Your Model

Begin by initializing the GPT model with OpenAI's GPT Builder. You can choose between various GPT model sizes, such as GPT-3, GPT-2, or even a smaller GPT model, based on your performance and resource requirements.

Load the Pre-trained Model Weights

Load the pre-trained model weights from OpenAI's GPT model. These weights have been trained on billions of text inputs and are a strong starting point for your custom model.

Prepare the Training Setup

Before fine-tuning your custom ChatGPT model, set up the training environment by specifying the necessary training parameters and hyperparameters, such as:

  • Batch Size: The number of training examples used for each update of the model weights.
  • Learning Rate: The step size used for optimizing the model weights.
  • Number of Epochs: The number of times the training loop iterates through the entire dataset.

Fine-Tune Your Custom Model

With your training setup ready, fine-tune your custom ChatGPT model on your prepared dataset using GPT Builder. This process updates the model weights based on the patterns in your dataset, making your ChatGPT tailored to your specific use-case.

Iterate and Optimize

Fine-tuning your ChatGPT model is an iterative process. Monitor your model's performance metrics, such as perplexity or loss, and adjust your hyperparameters as needed. You may need to experiment with different learning rates and batch sizes or even preprocess your dataset differently to achieve better results.

By building and fine-tuning your custom ChatGPT model, you can create a conversational AI model that delivers domain-specific, highly relevant, and accurate responses to your users.

Testing and Evaluating the Model

After building and fine-tuning your custom ChatGPT model, testing and evaluating its performance is crucial. This ensures that the model delivers high-quality responses and aligns with your project's goals. Here are some steps you can follow to test and evaluate your model:

Use Evaluation Metrics

Quantitative evaluation metrics, such as BLEU, ROUGE, or METEOR, can be used to assess the quality of your model's generated responses. These metrics compare the similarity between your model's responses and human-generated reference responses. While these metrics are helpful to gauge the performance of your model, they may not always capture the nuances and contextual relevance of the responses.

Try AppMaster no-code today!
Platform can build any web, mobile or backend application 10x faster and 3x cheaper
Start Free

Conduct Real-world Testing

Deploying your custom ChatGPT model within a controlled environment can provide valuable insights into its real-world performance. Interact with the model, pose various questions, statements, or scenarios, and analyze its responses' quality, relevance, and accuracy.

Perform Manual Evaluations

Sometimes, manual evaluation by domain experts or target users can offer valuable insights into the model's performance. These evaluations can help you uncover any discrepancies that automated metrics may have missed. It can also shed light on areas that need further improvement or refinement.

Iterate and Optimize

Based on the feedback and results gathered during the testing and evaluation phase, iterate on your custom ChatGPT model by adjusting your training setup, dataset, or training parameters as needed. Remember that creating a high-performing custom ChatGPT model requires continuous iterations and optimizations.

By thoroughly testing, evaluating, and refining your model, you can ensure that it closely aligns with your requirements and delivers an exceptional conversational experience to your users. And if you plan on integrating your custom ChatGPT into your software solutions, platforms like AppMaster make it easy to do so through their no-code, user-friendly interfaces.

Deploying the Custom ChatGPT

After building and fine-tuning your custom ChatGPT model, it's essential to deploy it effectively so it can be accessed and interacted with by users. Follow these steps to deploy your custom ChatGPT model:

  1. Choose a hosting environment: You can host your model on a local server or in the cloud using services like Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure. Consider your project's requirements, scalability needs, and budget when selecting your hosting environment.
  2. Configure the server: Create and configure the server environment to run your custom ChatGPT. This often involves installing necessary software dependencies, setting up the server with proper configurations, and securing the server with authentication and encryption mechanisms.
  3. Upload the model: Transfer your custom ChatGPT model to your chosen hosting environment, either over a secured file transfer protocol (SFTP) or using the cloud provider's object storage service (e.g., Google Cloud Storage, Amazon S3, or Azure Blob Storage).
  4. Expose the model via API: Create an API to handle users' requests and retrieve responses from the model. This can be achieved through standard frameworks like FastAPI, Django, or Flask for Python-based applications. Test the API's functionality before proceeding to ensure proper integration.
  5. Monitor performance: Regularly monitor your model's performance, resource usage, and uptime through server monitoring tools and custom scripts. Set up alerts to notify you in case of issues like excessive resource consumption, service outages, or anomalies in the model's behavior.
  6. Maintenance and updates: Ensure that your server environment and model implementations are up to date by periodically updating software dependencies, security patches, and regularly optimizing the custom ChatGPT model based on user feedback and performance data.

Integrating the Model with External Applications

Once your custom ChatGPT is deployed and accessible via an API, you can integrate it with external applications, such as chatbots, customer support systems, or content management platforms. Here are a few tips on integrating your custom ChatGPT into external applications:

  • Utilize existing plugin architectures: Many external applications provide plugin capabilities to extend their functionality. Develop custom plugins for these platforms that interact with your custom ChatGPT's API to offer seamless integration with minimal modifications to the existing system.
  • Integrate with chatbot frameworks: Implement your custom ChatGPT model within popular chatbot frameworks, such as Microsoft Bot Framework, Dialogflow, or Rasa, by using their native APIs or building custom integrations. This will allow the chatbot to leverage the capabilities of your custom ChatGPT model.
  • Connect to CRMs and customer support systems: Integrate your custom ChatGPT model with customer relationship management (CRM) systems and customer support platforms like Zendesk or Salesforce, using their APIs or custom connectors, to enable advanced conversational AI features, like case handling and ticket resolutions.
  • Go beyond text-based interactions: Amplify the capabilities of your custom ChatGPT by connecting it with voice-based platforms, like Amazon Alexa or Google Assistant, and using speech-to-text and text-to-speech functionality to enable voice interactions with users.
  • Integrate with AppMaster: Using AppMaster's no-code platform, you can seamlessly integrate your custom ChatGPT model with applications built on the platform for streamlined implementation of conversational AI in your software solutions. This streamlines incorporating chat interfaces and interactive elements within your apps.
Try AppMaster no-code today!
Platform can build any web, mobile or backend application 10x faster and 3x cheaper
Start Free

Optimizing Your Model for Better Performance

Continuous optimization is essential to get the most out of your custom ChatGPT model. Use these strategies to optimize your custom ChatGPT model for better performance:

  • Monitor user feedback: Pay close attention to user feedback and responses generated from your custom ChatGPT model. Identify areas where your model may require improvements, and use this information to guide further fine-tuning on your dataset.
  • Adjust hyperparameters: Experiment with altering hyperparameters, such as learning rate, batch size, and the number of training epochs, to find the optimal configuration for your custom ChatGPT model. Fine-tuning hyperparameters can lead to improved performance and efficiency of your model.
  • Implement model pruning: Reduce the size and complexity of your custom ChatGPT model by pruning unnecessary connections and parameters (weights) within the model's architecture. This can reduce the computational cost and resource usage while maintaining high-quality performance and output.
  • Utilize quantization: Quantization techniques can further optimize your model by reducing the precision of weights and activations in the model without significantly compromising performance. This may improve performance, lower latency, and reduced resource consumption.
  • Perform real-world testing: Test your model with real-world data and scenarios to uncover new optimizations and improvements. This ensures that your custom ChatGPT model remains up-to-date and attains the desired level of accuracy and reliability.

By following these guidelines, you can further enhance the performance and capabilities of your custom ChatGPT model, ensuring that it reliably meets the needs of your users and applications.

Conclusion and Next Steps

In this guide, we have provided an overview of building your own custom ChatGPT with OpenAI's GPT Builder. By creating a tailored conversational AI model, you can achieve improved performance and a more accurate understanding of your specific use case. As a next step, you should familiarize yourself with essential topics such as machine learning, natural language processing, and model evaluation to gain an in-depth understanding of the underlying concepts. Continuously iterate and improve your custom ChatGPT to maximize its effectiveness and fine-tune its capabilities to better serve your project requirements.

In addition, consider exploring other conversational AI models and framework alternatives to gain a broader perspective on the available technologies in the field. Engage with the open-source community to learn from their experiences and leverage their knowledge in fine-tuning and optimizing your custom ChatGPT.

Finally, consider utilizing platforms like AppMaster, a powerful no-code tool for creating web, mobile, and backend applications, to seamlessly integrate your custom ChatGPT into your projects. This will allow you to leverage the power of conversational AI into various aspects of your software solutions, delivering an improved user experience and optimizing your application's performance.

With the right approach and the willingness to experiment, you can create a powerful custom ChatGPT that serves your unique needs and helps your project stand out in the ever-evolving world of AI and technology.

How do I set up my development environment to work with GPT Builder?

To set up your development environment for working with GPT Builder, you'll need a powerful computer, an NVIDIA GPU, and the necessary software, such as Python, TensorFlow, and OpenAI library.

What can I use OpenAI's GPT Builder for?

OpenAI's GPT Builder allows you to create custom-tailored ChatGPT instances by fine-tuning the original GPT model on your specific dataset, offering optimized conversational AI experiences that better suit your project's requirements.

Can I integrate my custom ChatGPT with external applications?

Yes, you can integrate your custom ChatGPT with external applications through APIs or custom-built plugins, enabling seamless collaboration between the ChatGPT and other systems.

Can AppMaster be used for integrating a custom ChatGPT?

AppMaster's no-code platform allows seamless integration of custom ChatGPT models with applications built on the platform, providing a streamlined way of implementing conversational AI in your software solutions.

How do I select and prepare the dataset for training my custom ChatGPT?

Selecting the right dataset is crucial for building a custom ChatGPT. You can use pre-existing conversational datasets or create your own. Make sure to clean, preprocess, and format the dataset properly before training the model.

How do I test and evaluate the performance of my custom ChatGPT?

To test and evaluate your custom ChatGPT, you can use various metrics such as BLEU, ROUGE, or METEOR, and conduct real-world testing through user interactions and manual evaluations.

How can I optimize my custom ChatGPT for better performance?

Optimizing your custom ChatGPT involves fine-tuning the model, adjusting hyperparameters, optimizing response generation, and further customization based on your project's specific requirements.

What is ChatGPT?

ChatGPT is a conversational AI model that can engage in natural language interactions with users, providing human-like responses to questions, participating in discussions, and solving various tasks.

How can I fine-tune my custom ChatGPT model?

Fine-tuning your custom ChatGPT model involves training the model on your dataset, adjusting hyperparameters, and iterating through this process until the desired performance is achieved.

Related Posts

Create an App for Furniture Stores
Unlock the full potential of your furniture business with a dedicated app. Learn about the must-have features, benefits for customers and stores, and how AppMaster can help.
Data Handling with Kotlin Serialization
Delve into the nuances of Kotlin Serialization, a critical aspect for managing data in Kotlin applications. This comprehensive guide explores how to serialize and deserialize data effectively with Kotlin.
Theming with Jetpack Compose: Customizing Your App's Aesthetics
Unlock the secrets of theming in Jetpack Compose to customize your app’s aesthetics. Learn how to define themes, apply color schemes, and create a unique user experience with our in-depth guide on personalizing your app's interface.
GET STARTED FREE
Inspired to try this yourself?

The best way to understand the power of AppMaster is to see it for yourself. Make your own application in minutes with free subscription

Bring Your Ideas to Life

High‑quality bespoke cloning can be costly, with some services reported at up to $20,000 per minute.

In entertainment, voice cloning is used to simulate historical figures, create satirical content, localize films, and produce audiobooks, with platforms like Deepdub preserving timbre, rhythm, and intonation while reducing dubbing time and cost. [9][40].

Title:

Content: AI clones child’s voice in fake kidnapping scam

‘I never doubted for one second it was her,’ mother says

Anthony Cuthbertson
Thursday 13 April 2023 12:34
Comments

A mother has said she was “100 per cent” convinced by an AI voice clone of her daughter that scammers used in a faked kidnapping attempt.

Jennifer DeStefano from Arizona picked up a call from an unknown number and heard what she believed to be her 15-year-old daughter Brie “sobbing”.

The voice on the other end of the line said, “mom, I messed up”, before a male voice took over and made threatening demands.

“This man gets on the phone, and he’s like, ‘listen here, I’ve got your daughter’,” Ms DeStafano told local news show WKYT.

The apparent kidnapper told the mother: “You call the police, you call anybody, I’m going to pop her so full of drugs, I’m going to have my way with her, and I’m going to drop her off in Mexico.”

In the background, Ms DeStefano said she could hear her daughter saying “help me, mom, please help me” and crying.

“It was 100 per cent her voice,” Ms DeStefano said.

“It was never a question of who is this? It was completely her voice, it was her inflection, it was the way she would have cried – I never doubted for one second it was her. That was the freaky part that really got me to my core.”

The apparent kidnapper demanded $1 million for the daughter to be released, before lowering the figure to $50,000. Ms DeStefano only realised that her daughter was safe after a friend called her husband and confirmed that she was safe.

The scammer, who police are still investigating, appears to have used artificial intelligence voice clone technology, which has become increasingly competent in recent years at mimicking people’s voices.

It is also relatively easy to access and use, with AI tools freely available on the internet.

AI-generated voices have already been used in films to replicate actors like James Earl Jones who voiced the original Darth Vader character in the Star Wars franchise.

It has also been touted as a way for authors to produce audiobooks without spending hours in a studio reading their work.

The technology has also raised fears that it could be misused by scammers or people attempting to create deepfake videos, with one voice clone startup warning that it could be “harmful in the wrong hands”.

In a press release last year, the firm Respeecher said: “The widespread attention and adoption of deepfake technologies will accelerate the need to regulate the use of the technology.”

Thank you for registering

Please refresh the page or navigate to another page on the site to be automatically logged inPlease refresh your browser to be logged in

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

timbre
important vocal nuances
intonation

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

Accessibility use cases include reading assistance, translation, and generating audio in familiar voices for blind or visually impaired users. [2][10].

Title:

Content: Meta announces Voicebox, its generative AI model for audio

Today, Meta has announced its latest generative AI model, following on the back of ImageBind is Voicebox, which is designed to help creators with its ability to perform speech generation tasks such as audio editing, sampling and stylising, even if it wasn't specifically trained to do so through in-context learning.

Meta touts that this new AI model will have benefits to many people around the world, and uses examples such as helping visually impaired people to hear written messages from friends in their voices, as well as allowing people to speak foreign languages in their own voices.

The AI model itself can produce both high-quality audio clips, and edit pre-recorded audio to remove unwanted disruptions such as car horns while preserving the content and style of the audio while being multilingual, producing speech in six languages. Future developments for the model include giving natural-sounding voices to visual assistants, or non-player characters during games in the metaverse.

Meta has also compared Voicebox to other audio AI models out there, specifically naming Vall-E and YourTTS as competitors, demonstrating that Voicebox is more advanced and outperforms both models when comparing Word error rates and Style similarity.

Voicebox has been built on a Flow Matching model, which is Meta's latest non-autoregressive generative model, which can learn highly non-deterministic mapping between text and speech, enabling Voicebox to learn from varied speech data without it having to be carefully labelled allowing the data to be more diverse and on a larger scale.

Voicebox has been trained on more than 50,000 hours of recorded speech and transcripts from public domain audiobooks in English, French, Spanish, German, Polish, and Portuguese so far, and it can also predict a speech segment when given the surrounding speech and the transcript of the segment.

Lastly, Meta goes on to comment that while the technology can bring in a new era of generative AI for speech, it could bring the potential for misuse and unintended harm.

In the research paper that Meta will be sharing about Voicebox, it will include detail on how it has built a highly effective classifier which can differentiate between authentic speech and Voicebox-generated speech.

Meta will not be making the AI program itself available for public use, nor will it be releasing the source code.

Report a problem with article
Next Article

Nvidia RTX 4090 16-pin 12VHPWR connectors still burning: First case of PSU-side melting

Previous Article

Xbox Game Studios head insists cloud gaming is still "a very, very small market"

Education and e‑learning leverage AI voices for multilingual courses, digital marketing and YouTube content, and conversational practice, with platforms such as Loora using AI‑driven voice interactions to improve English skills. [13].

Title:

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

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

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

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

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

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

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

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

How will AI Voice help educators with building courses?

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

Enterprise adoption is growing rapidly, with ElevenLabs reporting usage by employees at 41% of Fortune 500 companies.

Title:

Content: Grow with AppMaster.
Become our partner
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.
Related posts
OpenSSF partners with CISA to develop new package repository security framework
A collaborative initiative between OpenSSF and CISA has led to the development of package repository security principles.
Kobiton open source AI-driven Appium script generation tool
Kobiton is shaking up the mobile testing landscape by open-sourcing its Appium scripting tools, increasing automation, and encouraging community-driven development.
Google ’ s Gemini Advanced: Using Ultra 1.0 to Boost AI Assistant Capabilities
Google has ushered in a new era of digital assistance with Gemini Advanced in the Google One AI Premium Plan.
Unlock advanced features like complex coding and creativity for just $19.99 per month.
Start for free
Are you inspired to try it yourself?
The best way to learn about the power of AppMaster is to experience it firsthand.
Free subscription, make your own app in minutes
Turn your ideas into reality

The same realism fuels misuse, as fraudsters can clone voices from clips as short as 3 to 20 seconds to impersonate family members or public figures. [5][20].

Title:

Content: Scammers can use AI tools to clone the voices of you and your family—how to protect yourself

A robocall impersonating President Joe Biden urged New Hampshire voters not to participate in Tuesday's presidential primary — and it probably won't be the last AI voice scam this election season.

"Of course, this will be used by foreign nation states just like the trolling farms they already have. This is just another weapon in the arsenal," Adrianus Warmenhoven, a cybersecurity expert at NordVPN, tells CNBC Make It.

The fraudulent robocall begins by saying, "What a bunch of malarkey," in a voice that sounds like President Biden's, according to NBC News. The call then instructs recipients to "save your vote for the November election" and refrain from participating in the nation's first presidential primary, which is when voters choose which candidate they would like to be their political party's nominee in the general election.

New Hampshire's Attorney General's office says it has launched an investigation following a series of complaints about the robocalls.

"Although the voice in the robocall sounds like the voice of President Biden, this message appears to be artificially generated based on initial indications," the attorney general's office said in a Jan. 22 statement. "These messages appear to be an unlawful attempt to disrupt the New Hampshire Presidential Primary Election and to suppress New Hampshire voters."

Thanks to the rapid development of the type of AI technology used to clone and mimic people's voices, these types of AI-powered schemes are becoming more common — and scammers aren't just spoofing well-known public figures.

In March, the Federal Trade Commission issued a consumer alert warning people that scammers could target them by using AI technology to clone the voice of a family member in order to convince them to send the scammers money.

How to protect yourself from AI voice scams

Although it's getting harder to differentiate between what's real and what may be an AI-generated deepfake, there are a couple of steps you can take to protect yourself.

1. Fact-check and verify

When it comes to AI voice scams like the one involving Biden, you should double check that what you're hearing is actually correct, Warmenhoven says.

Although the spoofed version of President Biden voice told New Hampshire voters to "save" their votes for the November general election, a quick Google search reveals that registered Republicans and undeclared voters could cast their ballot in Tuesday's primary.

If you suspect you're being targeted by a cybercriminal, you can also check online to see if there have been any recent reports of AI-generated voice scams, Warmenhoven says.

2. End the call

If you decide to answer a call from an unknown number and it sounds like a panicked family member is asking you for money, try not to panic yourself.

Instead, end the call and try calling or texting the person using the number they've given you, rather than the one that called, to check that they're OK, Warmenhoven says.

The same goes if you receive a call from a scammer pretending to be your bank. Don't immediately believe their claims. Instead, end the call and call the number listed on your bank's website or on the back or your debit or credit card, he says.

It's especially important to get off the phone with these types of scammers, because they don't need an especially long clip of your voice in order to use AI to clone it.

"Even if you just say 'Hello? Is anybody there ?' or just mumble something, you'll give up lots of words and inflections in your voice and then [a scammer] can clone your voice," Warmenhoven says.

In May, McAfee researchers found that free online tools could be used to clone someone's voice using just three seconds of audio, per the computer software company's "The Artificial Imposter" report.

"Advanced artificial intelligence tools are changing the game for cybercriminals. Now, with very little effort, they can clone a person's voice and deceive a close contact into sending money," Steve Grobman, McAfee's chief technology officer, said in the report. "It's important to remain vigilant and to take proactive steps to keep you and your loved ones safe."

DON'T MISS: Want to be smarter and more successful with your money, work & life? Sign up for our new newsletter!

Want to land your dream job in 2024? Take CNBC's new online course How to Ace Your Job Interview to learn what hiring managers are really looking for, body language techniques, what to say and not to say, and the best way to talk about pay. Get started today and save 50% with discount code EARLYBIRD.

Contact Us

What are some risks regarding AI voice clning?

What is necessary for voice cloning to work?

The FTC warns that AI voice clones can turbocharge fraud, and fake kidnapping calls have used cloned voices to convincingly imitate loved ones.

Title:

Content: Tech
Artificial Intelligence

AI voice clones are turbocharging scams, top FTC official warns

"We need to be vigilant early," FTC Chair Lina Khan said.
By Tim Marcin  on
FTC Chair Lina Khan warned AI is turbocharging scams. Credit: Saul Loeb-Pool/Getty Images

AI tools, particularly voice clones, are supercharging scams, FTC Chair Lina Khan warned.

Speaking at an AI and venture capital event on Thursday, Khan warned officials will have to be proactive to stop AI-powered fraud, Bloomberg reported.(opens in a new tab)

She noted that they are already seeing AI "turbocharge" scams, using voice clones that can copy family members in distress as an example, according to Bloomberg.

"We need to be vigilant early," Khan said, according to Bloomberg. "If anything you need to be especially vigilant on the front-end because it’s much more difficult to solve these problems after."

Voice clones have proven capable of fooling folks. A CNN report (opens in a new tab)noted that fake kidnapping calls demanding ransoms using the tech were becoming more common. Jennifer DeStefano told the outlet her story of getting a call demanding $1 million for their daughter before realizing the caller had used AI to copy her voice.

"The voice sounded just like Brie’s, the inflection, everything," she told CNN.

AI voice clones have even made popular songs featuring fake versions of real artists. Even a relatively easy-to-spot fake image of the Pentagon being attacked caused a real dip in the stock market.

"As this stuff becomes more embedded in how daily decisions are being made, I think they invite and merit a lot of scrutiny," Khan said, according to Bloomberg. "Those problems and concerns are quite urgent and I think enforcers, be it at the state level or the national level, are going to be acting."

Tim Marcin

Tim Marcin is a culture reporter at Mashable, where he writes about food, fitness, weird stuff on the internet, and, well, just about anything else. You can find him posting endlessly about Buffalo wings on Twitter at @timmarcin(opens in a new tab).

Recommended For You
Snapchat's My AI has users reaching their snapping point

Fake Pentagon explosion photo caused a real dip in the stock market

Snapchat's AI chatbot is rolling out to all users globally

6 ways the White House is reining in AI

Trending on Mashable
Wordle today: Here's the answer and hints for June 4

NASA's finally talking about UFOs with Americans. Here's what they said.

Spider-Punk is the real hero of 'Spider-Man: Across the Spider-Verse'

Wordle today: Here's the answer and hints for June 3
The biggest stories of the day delivered to your inbox.
This newsletter may contain advertising, deals, or affiliate links. Subscribing to a newsletter indicates your consent to our Terms of Use(opens in a new tab) and Privacy Policy(opens in a new tab). You may unsubscribe from the newsletters at any time.
Thanks for signing up. See you at your inbox!

Regulators are responding, including US actions banning AI‑generated voice calls and FCC rulings applying the TCPA to AI‑generated voices, which require prior express written consent for robocalls. [16].

Title:

Content: Moving at rapid speed, the Federal Communications Commission (FCC) has just announced its unanimous adoption of a new Declaratory Ruling finding that voice calls using artificial intelligence (AI)-generated voices fall under the Telephone Consumer Protection Act (TCPA).

The ruling takes effect immediately and gives state attorneys general powerful new tools to go after voice cloning scams. Under FCC rules, telemarketers that use robocalls subject to the TCPA are required to obtain prior express written consent from the consumer unless an exemption applies. The TCPA has always prohibited the use of both prerecorded and artificial voices but advances in AI-generated voices have prompted the FCC to specifically address their use.

In recent years, scammers and other parties have begun using AI to create fake and even "cloned" artificial voices, including those of celebrities, politicians, and even a call recipient's family member. In this election season, there has been increasing concern about the use of voice clones to engage in voter suppression schemes.

Concerned about the potential malevolent uses of these AI-generated voice calls, the FCC issued a Notice of Inquiry (NOI) in November on the topic of "Implications of Artificial Intelligence Technologies on Protecting Consumers from Unwanted Robocalls and Robotexts." In the NOI, the FCC asked questions regarding the use of "AI-influenced" technologies in robocalling. A coalition of 26 state attorneys general, as well as a telecommunication carrier trade group, strongly urged the FCC to take action to give the attorneys general clear authority to act against AI-generated robocall violators.

The FCC now has made clear that the use of voice cloning in telephone calls and texts falls within the FCC's statutory authority under the TCPA. A major intent of the ruling is to communicate that the TCPA "does not allow for any carve-out of technologies that purport to provide the equivalent of a live agent, thus preventing unscrupulous businesses from attempting to exploit any perceived ambiguity in our TCPA rules."

As FCC Chairwoman Jessica Rosenworcel explained, "with this Declaratory Ruling, we will have another tool to go after voice cloning scams and get this junk off the line."

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

Detection and defense tools are emerging, including Pindrop’s winning solution in the FTC Voice Cloning Challenge, Veridas Voice Shield making judgments from 3‑second samples, AI Detect’s classifiers, DeFake’s watermarking proposal, and Truecaller’s real‑time AI Call Scanner. [21].

Title:

Content: Advertisement
Technology and Science
A very important feature.
This is the new Truecaller app!
29-05-2024 | 14: 00
A-
A +
photos 0
A +
A-
Caller ID service Truecaller has launched the world ’ s first AI voice detection feature, the “AI Call Scanner ”, to enhance its anti-spam and fraud capabilities.
This innovative tool uses artificial intelligence to identify sounds made by artificial intelligence during phone calls and alert users in real time.
Advertisement
Voice scams using artificial intelligence that mimic human voices for financial extortion have been on the rise since they first appeared around 2019.
Fraudsters often use social media to collect voice samples and train AI to clone voices, which they then use to deceive a person ’ s family.
Aware of the growing threat, Truecaller has developed an AI Call Scanner tool to combat these complex scams.
Truecaller designed the “AI Call Scanner ” feature to distinguish between human sounds and sounds made by artificial intelligence, protecting users from scams.
The service has integrated this feature into its Android app, part of the premium subscription, and is rolling out in the United States first, followed by India and other major Truecaller markets.
When receiving a suspicious call, users can tap a button within the app to activate the “AI Call Scanner ” and the call then integrates with a secure line that records a sample of the caller ’ s voice.
This sample is analyzed by Truecaller ’ s advanced AI model, which quickly determines whether the voice is human or artificial intelligence.
In order to use the AI Call Scanner feature, Truecaller must be set as your default calling app, and if the call looks suspicious, you can tap the Start AI Detection button in the app to briefly suspend the call while the AI analyzes the audio.
A message appears saying “analysis, ” indicating that the AI is working, and during the call you receive a message stating whether the sound is human or made by the AI, allowing you to take immediate action.
Truecaller says it is also exploring ways to improve the AI Call Scanner feature, including enhancing accuracy, reducing response times and adapting to new audio compositing technologies.
(aitnews)
Go ahead.
Advertisement
Our news via your email
SIGN UP

Voice cloning raises complex legal questions about consent, ownership, and copyright, with concerns that platforms can appropriate unique artist voices without compensation and with unresolved voice rights in music and film. [11].

Title:

Content: "We meet."
Om Kulthum sings "Boss Wawa"
I'm sorry.
Barwin Habib
Imagine that in your mobile phone an application through which you can choose any song you like - or hate - no difference - in the voice of your favorite singer, so you hear, for example, Om Kulthum singing "Bose El Wawa" by Haifa Wahbi, or Sabah Fakhri Salten in the song "Local Sugar" by Hassan Shakoush.
The issue is not a joke nor a rarity as was done by the copycats when singing a song of a known singer with the voice of another singer and his movements in order to laugh, but by the blessing of artificial intelligence this is achieved for those who are proficient in using it, and soon it will be available in our phones for free, so small and large can use it easily as he uses chat applications.
If hologram evokes the singer ’ s body in a three-dimensional image using laser beams as if he were present with us, it is now possible to make him sing what the user wants.
Perhaps what the composer Amr Mustafa did when he published a promotional advertisement for a song entitled “Aftakrlk A ”, from his melodies and the sound of Umm Kulthum, sounded a great alarm about the chaos that will affect our musical heritage. Western artists and musicians have been alerted to this upcoming monster. A large group of them launched the“ Human Art ” campaign so that “Artificial Intelligence ” does not kill human creativity. Artists may have to fight a battle to defend their work against artificial intelligence.
And this reproduction of the voices of singers is not only about the heritage and emotional aspect, and beyond our doubt, can the voice reproduced by artificial intelligence carry the feelings and emotions of the real artist?
The issue has an important legal aspect related to the rights of the voice itself, which opens the door to infringement and graft.
The big problem is that the big boom in cloning artists ’ voices is far faster than the laws that protect and regulate them, and it will eliminate entire professions such as the music distributor ’ s profession, what the distributor has been studying for years in the higher music institutes, any free music distribution program can do in just a few minutes.
I would no longer be surprised if I, who spent half my life in the visual media, found my voice on a podcast I had never heard of, say, ice hockey.
I am not against technology or against evolution, but I think that artificial intelligence is a great leap in the march of humanity, I only hope that it will leave us something of its nature, how much I fear that what happened to the artists what happened to Hapanga, who was wearing a necklace in his neck to identify himself, and when he saw it in the neck of his brother asked him surprised: "Brother you are me?"
I wouldn ’ t be surprised if I found my voice, which I ’ ve spent half my life in visual media, on a podcast I ’ ve never heard of, for example, ice hockey.
@ DrParweenHabib1
To read the author ’ s previous articles, please click on his name.
Print

High‑profile disputes highlight these issues, including Scarlett Johansson’s allegations over unauthorized vocal resemblance and broader celebrity deepfake deceptions.

Title:

Content:

When tech goes bad: Celebrities and the dangers of deepfake technology

Find out how the use of deepfake technology is causing celebrities distress and bringing up important ethical issues in the digital era, as seen in the cases of Scarlett Johansson and Rashmika Mandanna.

By  Varun ShethMay 22, 2024 5:36 PM
The recent controversy around Scarlett Johansson's artificial intelligence (AI) voice resemblance highlights the widespread danger that deepfake technology poses to prominent personalities. (Image sourced via Forbes)

Artificial intelligence breakthroughs have given rise to deepfakes, which can produce realistic-looking but completely fake material. Although there are innovative and entertaining uses for this technology, its abuse has created serious moral and legal issues. Deepfake deceptions have made celebrities in particular great targets, with potentially disastrous consequences for both their personal and professional life. The recent controversy around Scarlett Johansson's artificial intelligence (AI) voice resemblance highlights the widespread danger that deepfake technology poses to prominent personalities.

The video that started the deepfake controversy featured British-Indian influencer Zara Patel, whose face had been Photoshopped to seem like actress Rashmika Mandanna. Following the outcry caused by the viral video, Mandanna expressed her extreme distress. Her comment brought to light the horrifying consequences of deepfake technology. Similar to this, there have been concerns raised regarding the improper use of deepfake technology in the entertainment business when an altered photo of Katrina Kaif from her upcoming film "Tiger 3" appeared online.

Hollywood legend Tom Hanks was forced to post a caution on social media earlier this month over the usage of an AI-generated image of himself in a misleading dental plan advertisement. Hanks stressed in a post to his 9.5 million Instagram followers that his picture was being used without permission.

Despite legal obstacles, Scarlett Johansson encountered deepfake issues when her face was transformed for pornographic films. She acknowledged the difficulties in taking legal action against these AI-generated movies and emphasised the size of the internet and the difficulties in policing content of this kind. Johansson had yet another incident lately when her vocal resemblance appeared in OpenAI's ChatGPT 4.0 system. This time, she filed a lawsuit, which ultimately forced OpenAI to remove the voice.

Jimmy Donaldson, better known online as Mr. Beast, was the target of a dishonest TikTok advertisement that used fraudulent AI to promise viewers $2 iPhones. This instance demonstrated how frauds linked to deepfake may propagate bogus information and trick viewers into accepting fictitious claims. Donaldson's experience shows how deepfakes may be used in scams, making attempts to oversee and regulate the technology even more difficult.

Tags
First Published on May 22, 2024 5:36 PM

More from Storyboard18

How it Works

Shah Rukh Khan admitted to Ahmedabad hospital due to heatstroke

How it Works

ASCI finds healthcare and illegal betting top violative sector in FY24

How it Works

TRAI hosts meeting of regulators to combat spam calls, messages

How it Works

BJP’s political ads hit it off with the public, six in ten say it influenced them to cast a vote

How it Works

Failed Zee-Sony merger cost Zee a whopping Rs 432 crore

How it Works

Celebrity image protection explained: Understanding personality rights and legal options

How it Works

Big tech's data advantage and opaque algorithms threaten fair competition: CCI’s Ravneet Kaur

Companies may face liability for chatbot and AI system outputs, and traditional legal frameworks do not fully address accountability for generative systems.

Title:

Content: When chatbots promise refunds are companies on the hook? Air Canada recently learned firsthand how chatbot legal issues can send a company to court.

After being misled by the airline chatbot about its bereavement travel policy, Jake Moffatt, who booked a flight following a family loss, fought for a partial refund. Despite the chatbot's incorrect guidance, the airline initially resisted refunding, suggesting the chatbot's advice was separate from the airline's official policy.

The case, which reached Canada's Civil Resolution Tribunal, highlighted the responsibility of companies for their chatbots' information, leading to a ruling in Moffatt's favor for a partial refund and additional damages.

This incident serves as a crucial reminder for Texas businesses about the unpredictability and potential legal implications of using artificial intelligence, especially chatbots, in customer service and business operations.

AI Chatbot Liability Problem

The integration of AI chatbots into customer service and business operations introduces a complex web of liability issues. When a chatbot like Air Canada's provides incorrect information or makes unauthorized decisions, the question arises: who is legally responsible?

The legal community is grappling with this question, as traditional laws don't fully address the autonomous actions of AI systems. Businesses must navigate these uncharted waters carefully, ensuring their AI systems are well-regulated and monitored to prevent the dissemination of false or legally binding information inadvertently.

Moreover, the liability problem extends beyond mere misinformation to include issues related to data security and privacy breaches. Chatbots, by design, interact with users and collect data, posing a risk if this data is mishandled or exposed. The potential for chatbots to be exploited for phishing attempts or to inadvertently disclose sensitive information requires businesses to implement stringent data protection measures.

Other Generative AI Issues Emerging for Business Owners

Beyond chatbots, generative AI technologies are introducing new layers of complexity for business owners. These systems, capable of creating content that resembles human output, raise significant concerns about copyright infringement, authenticity, and ethical use. For instance, generative AI tools that produce text, images, or music could inadvertently violate existing copyrights, leading to legal disputes and significant financial liabilities for businesses.

The issue of deepfakes—hyper-realistic digital content generated by AI—presents another challenge. These can be used to create misleading or defamatory content that damages reputations and misleads consumers. Businesses using generative AI must navigate these ethical and legal minefields, ensuring their use of AI respects intellectual property rights and does not contribute to the spread of misinformation.

How to Avoid Legal Trouble When Considering Chatbots and Other AI

The evolving nature of AI technology means that legal precedents and regulations are continuously playing catch-up. Businesses must stay informed about legal developments and be prepared to adjust their AI strategies accordingly. This might involve engaging in active dialogue with legal experts, regulatory bodies, and AI developers to advocate for clear guidelines and safeguards that address the unique challenges posed by AI chatbots.

Furthermore, the transparency and explainability of AI decisions are becoming critical issues. As AI systems play a more significant role in business operations, the ability to understand and explain how AI decisions are made is crucial for compliance with regulations and for maintaining public trust. Businesses must ensure their AI systems are not only effective but also transparent and accountable.

Here are additional steps business owners can take:

  • Have a plan – To minimize legal risks, businesses should adopt a proactive and strategic approach to AI implementation. This involves conducting thorough risk assessments to identify potential legal issues and integrating robust compliance measures from the outset. Regularly updating these measures in line with evolving AI capabilities and legal standards is essential.
  • Clarify the policy – Creating clear terms of use and privacy policies that inform users about the role and limitations of AI in their interactions with the business can provide an additional layer of legal protection.
  • Educate your team – Investing in AI literacy and training for staff can help ensure that AI tools are used responsibly and in compliance with legal and ethical standards.
  • Employ human oversight – Human review can catch errors or unethical content generated by AI, providing a safeguard against potential legal and reputational damage. Establishing a feedback loop where AI performance and its implications are continuously monitored and adjusted based on user interactions and feedback can also help mitigate risks.

Conclusion

The Air Canada incident is another wake-up call for businesses integrating AI into their operations. As AI technologies become more sophisticated and widespread, the legal implications and responsibilities of businesses will only increase. To ensure that your business is prepared and protected, consider consulting with legal experts who specialize in this area.

Originally published March 15, 2024

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

OpenAI requires explicit consent for Voice Engine, watermarks generated audio for origin tracing, and recommends phasing out voice‑based authentication for sensitive access.

Policy experts urge regulations to manage deep counterfeiting and voice copying, define legal versus illegal uses, and ensure enforceable compliance.

Title:

Content: Freedom Square (Beishe Review) Policy response strategy for artificial intelligence deep counterfeiting and voice copying technology
◎ Cai Yue Ting
Deep hypocrisy and voice copying are technologies that use artificial intelligence to generate fake or manipulative media that can be used for a variety of purposes, including entertainment, education, and journalism.
If it is abused for fraud and the dissemination of false information, it will damage the reputation and rights of the individual, and it will affect social order and national security.
Because there are major potential hazards, it is necessary to formulate relevant regulations and effective management, and it can promote the healthy development of this innovative industry.
Consolidating practice cases to standardize policy measures to manage deep counterfeiting and voice copying can go hand in hand with the following aspects:
I. Regulations:
The content of the bill should include: (1) clearly stipulate the legal and illegal use of deep counterfeiting and voice copying to protect personal and national security and rights; (2) establish effective enforcement mechanisms and regular amendments to ensure the effective implementation of the law and adapt to the rapid development of technology; (3) use ethics education and advocacy; and (4) specify appropriate punitive measures.
2. Technical supervision:
(1) Establish an effective enforcement mechanism, consisting of experts with professional knowledge and technical ability, to (1) supervise the development and application of deep counterfeiting and voice reproduction technology to ensure that the use of the technology complies with laws, regulations and ethical standards; (2) adhere to the principle of minimum intervention, and strike a balance between protecting personal privacy and preventing abuse; and (3) promote the sound development of the industry.
Restrictions on use: Restrictions on the use of deep counterfeiting and voice copying technologies, especially in sensitive areas such as finance, politics, law, and medicine, and where they may have a serious impact on personal privacy.
Transparency and Authentication: (1) Require developers and users of deep counterfeiting and voice copying technologies to provide transparency to ensure that users are informed and consent to the use of their data.
(2) Establish a certification mechanism to ensure that only accredited institutions and individuals can use these technologies.
(4) Technical research: Encourage research on deep counterfeiting and voice copying technologies, especially research on detecting and preventing abuse, and research on how to protect personal privacy.
Participation, use of ethics education and public awareness: to strengthen the education of the public and related industries, and to raise awareness of the potential risks of deep counterfeiting and voice copying technology.
Authorities should provide corresponding preventive measures and education and training.
The development of deep counterfeiting and voice reproduction technology has brought many potential risks, but it is also an integral part of the country ’ s sustainable development.
This industry requires the participation of multiple stakeholders, how to ensure that these technologies are used responsibly and ethically through legal, technical and educational means, and to minimize their potential hazards, to the rapid and vigorous development of the industry is a matter of urgency.
(The author is Deputy Secretary General of Beishe, Director of Research and Development of the Institute for Information Technology)
No need to smoke, no need to grab, now use the APP to watch the news, guarantee the daily winning point I download the APP
I've added friends, thank you.
Welcome to [Free Commentary]
It's a compliment. Good.
It has been praised, thank you.
Editor 's Choice

Ethical risks include privacy invasion, manipulation via deepfakes, lack of informed consent, cultural insensitivity, and the exploitation of voices of deceased individuals. [14][10].

Title:

Content: Amazon Alexa reproduces the voice of friends and relatives to remember the dead or help to cheat?
Author: 01 Weekly Report
Published: Updated:
Tech giant Amazon last week hosted its annual developer conference re: MARS to introduce AI applications in machine learning, automation, robotics and space.
A short demonstration video was shown.
A child asked the Panda ’ s child-themed voice assistant, “Alexa, can grandmother continue to tell me the story of The Wizard of Oz? ” Alexa answered“ OK ” with its preset voice line, then switched to another voice that sounded closer to humans and read the plot of the Cowardly Lion seeking self-confidence.
Rohit Prasad, Alexa ’ s chief scientist, introduced at the conference that Alexa can mimic a voice line with less than a minute of recorded content: “The way we do this is by defining the problem as a speech-to-speech task, not a speech-generating path. ”
Amazon has in the past developed voice synthesis technology that allows Alexa to mimic the voice of basketball star Shaquille O ’ Neal or comedian Melissa Mccarthy.
At that time, the practice was relatively backward, requiring someone to record a large amount of audio for a long time.
In contrast, Alexa, the new voice imitation function, is said to be based on recent advances in text-to-speech technology, which can generate high-quality, like-for-like sound lines with less data.
Alexa Chief Scientist Rohit Prasad told re: MARS 2022 that the company is developing AI to reproduce the voice of the deceased family and friends, hoping to deepen the “humanity ” of the AI voice assistant. (Amazon re: MARS 2022 YouTube clip screenshot)
For example, he claims that this advancement in AI can enable consumers to maintain “lasting personal relationships ” with their deceased relatives:“ While AI cannot eliminate the pain of losing a loved one, it can definitely make memories last … There is no doubt that we are living in the golden age of AI, and our dreams and science fiction are becoming a reality. ”
After Amazon announced the latest feature of Alexa, it also caused a lot of negative reviews on the Internet, from the social media Twitter, users criticized the feature as "disturbing", "sick", or they do not want it.
As Tama Leaver, a professor of Internet studies at Curtin University in Australia, points out, the line between humans and machines is beginning to blur in such applications: “You won ’ t remember whether you ’ re talking to Amazon ’ s data collection service or to the voice of your grandparents or a deceased loved one. ”
In a way, it ’ s kind of like the story of Black Mirror. ”
Some scholars have pointed out that the use of AI to reproduce voice lines involves security and ethical issues such as fraud risk, informed consent, and ownership, and should be considered early before such technology is popularized. (Replica)
Leaver also pointed out that the new feature of Alexa has an informed consent problem in the production.
Using the data of the deceased in this way, he said, “is both creepy and unethical, because the deceased himself may not have thought that his data would be so used after death. ”
Subbarao Kambhampati, a professor of computer science at the University of Arizona, agrees: “For people who are grieving, this technology may actually help, as we look back and watch videos of the deceased.
But it also raises serious ethical questions, such as, is it okay to do this without the consent of the deceased? ”
Some scholars and experts have pointed out that AI simulation sound lines may have security and ethical issues.
In terms of security, there are concerns that this technology could be used as a fake scam.
Rachel Tobac, CEO of security firm SocialProof Security, warns that society is not prepared for the risk that this voice technology will be exploited by criminals: “If cybercriminals can easily and reliably copy another person ’ s voice with a small number of voice samples, they can use that voice sample to impersonate others, which could lead to fraud, data and account theft. ”
For more information, please read the 323 issue of Hong Kong 01 e-Weekly (27 June 2022), "Amazon Alexa Recurring the Voice of Friends and Family to Remember the Dead or Help to Cheat?".
Click here to try our weekly newsletter for more in-depth coverage.
You may be interested

Researchers and startups warn of potential harm, calling for responsible development, technical transparency, and robust safeguards to minimize misuse. [6][12].

Title:

Content: Urgent.
Chairman of Wafd Party
Dr. Abdul Sindh Yamama
Chairman of the Board of Directors
Dr. Ayman is an accountant.
Editor-in-Chief
I'm sorry.
My grandfather, Zainuddin.
Chairman of Wafd Party
Dr. Abdul Sindh Yamama
Chairman of the Board of Directors
Dr. Ayman is an accountant.
Editor-in-Chief
I'm sorry.
My grandfather, Zainuddin.
What is the future of artificial intelligence?
As part of our year-end story package, ChatGPT commissioned us to write a guest post about the future of generative AI.
The claim asked for a 1,200 word essay (a number that was undermined by a large margin) exploring the potential negative and positive consequences of the technology.
We then asked her to include real-world examples, apparently beyond her abilities.
We also asked her to include a section on the recent Sam Altman disaster, which, as you will soon read, was also not a topic she could describe privately.
Below is the unedited output with light formatting changes.
Navigating the future of generative AI: balancing exciting possibilities with potential pitfalls
Generative Artificial Intelligence (AI) has emerged as a powerful force, reshaping the technological landscape thanks to its ability to independently create content.
From language models such as GPT-3 to image generation algorithms, generative AI holds enormous promise for the future.
However, this promising future is not without challenges.
In this article, we will explore the potential negative consequences and the most exciting possibilities of generative AI, with the aim of balancing optimism with caution.
In addition, we will address the recent leadership shift involving Sam Altman at OpenAI, highlighting ethical considerations associated with AI development.
Sam Altman ’ s Leadership Transformation: Lessons in Ethical Artificial Intelligence
In recent months, the AI community has seen a major leadership shift at OpenAI that Sam Altman has been involved in.
The CEO, known for his influential role in guiding OpenAI initiatives, faced a period of controversy over his subsequent dismissal and reappointment.
This incident highlighted the challenges associated with ethical considerations in the development and management of AI.
Addressing ethical concerns: Sam Altman ’ s leadership transformation has led to a reassessment of ethical considerations in AI development and regulatory decision-making.
The incident raised questions about transparency and accountability and the need for strong ethical frameworks to guide the development and deployment of AI technologies.
Transparency and accountability: The leadership transition emphasized the importance of transparency in organizational decision-making, especially in contexts involving AI technologies with wide-ranging implications.
He highlighted the need to hold leaders and organizations accountable for their actions and to ensure that ethical guidelines were followed.
Community Engagement: The controversy surrounding Sam Altman ’ s leadership transformation has also highlighted the importance of involving the wider community in decisions related to AI development.
The call for more inclusive decision-making processes has gained momentum, reinforcing the idea that diverse perspectives play a crucial role in overcoming the ethical challenges associated with AI technologies.
Application for Photoshop Geneative AI:
Photoshop (AI Wave: “The Future of Generative Artificial Intelligence in Manga Style ”)
Possible negative consequences
Ethical Concerns and Prejudice
One of the primary concerns with generative AI is its susceptibility to biases found in training data.
If the data used to train these models reflects societal biases, AI may inadvertently perpetuate these biases and amplify them in their resulting content.
Addressing this problem is critical to preventing AI systems from inadvertently promoting and spreading harmful stereotypes.
Security Threats and Deep Counterfeiting
The ability of generative AI to produce highly realistic and compelling content raises serious security concerns.
Deepfakes, for example, are images or videos created by artificial intelligence that manipulate content and superimpose it on real footage.
This technology can be exploited for harmful purposes, such as creating fake news, impersonating individuals or spreading misleading information.
With the development of generative AI, the challenge of distinguishing between real and fake content has become increasingly difficult.
Invasion of Privacy
Advances in generative artificial intelligence also raise concerns about privacy violations.
The ability to create realistic images and videos of individuals who have never been involved in creating such content poses a risk to personal privacy.
Protecting individuals from the unauthorized use of their images in AI-generated content will be a pressing issue in the coming years.
Unemployment and economic turmoil
The automation capabilities of generative AI – the displacement of the workforce in some industries – may be driving.
Jobs that involve routine and repetitive tasks, such as content creation, may be at risk.
Balancing technological progress with societal well-being will be a challenge to ensure that AI complements human work rather than replaces it.
Ethical and ethical dilemmas
As AI systems become more efficient at producing content that mimics human creativity, ethical questions arise.
For example, who owns the rights to art or literature generated by artificial intelligence?
Identifying the legal and ethical implications of creations produced by non-human entities challenges our traditional understanding of authorship and intellectual property.
That's what generative artificial intelligence thinks.
Photoshop (Artificial Intelligence Wave: "Future Artificial Intelligence Utopia")
The most exciting possibilities.
Enhancing creativity and productivity
Generative AI has the ability to amplify human creativity and productivity by automating mundane tasks, allowing individuals to focus on the most complex and strategic aspects of their work.
In areas such as content creation, design and marketing, AI can help and inspire, leading to an increase in innovation and efficiency.
A revolution in health care
The future of generative AI promises breakthroughs in healthcare, from drug discovery to personalized medicine.
AI models can analyze large data sets, identify patterns, and propose new solutions, dramatically accelerating the pace of medical research and improving patient outcomes.
Custom User Experiences
As generative AI continues to evolve, it can provide highly customized and tailored experiences for users.
From adaptive learning platforms to content recommendations, AI systems can understand individual preferences and behaviors, providing a smoother and more engaging user experience.
Collaboration between Human and Artificial Intelligence
Instead of replacing human roles, generative AI is likely to foster collaboration between humans and machines.
AI tools can act as creative partners, helping professionals in various fields achieve results that would not be possible by traditional methods alone.
This collaborative approach can lead to unprecedented levels of innovation.
Innovations in art and entertainment
Generative AI has already made waves in the art world, creating unique pieces that challenge traditional notions of creativity.
In the entertainment industry, AI-driven content creation can open up new horizons for storytelling, virtual worlds, and interactive experiences, pushing the boundaries of what is possible in these areas.
CONCLUSION
The future of generative AI is a double-edged sword, offering exciting possibilities and potential pitfalls.
As we navigate this technological landscape, it is important to recognize and address the ethical concerns and negative outcomes associated with generative AI.
Balancing innovation and responsible development is essential to harnessing the full potential of AI while mitigating its risks.
By fostering interdisciplinary collaboration, implementing ethical guidelines, and investing in research to address biases and security threats, we can pave the way for a future where generative AI enhances human creativity, productivity, and well-being.
The recent leadership shift that Sam Altman participated in serves as a reminder of the importance of ethical considerations in the development of AI, urging the industry to learn from the mistakes of the past and shaping a collective future where AI benefits humanity responsibly.

What are some risks regarding AI voice clning?

In education settings, UNESCO calls for clear guardrails for generative AI in schools, including data privacy protections, age limits, ethical validation, and transparency whenever AI‑generated content is used.

Title:

Content: UNESCO calls for regulations on use of GenAI in schools

The United Nations Educational, Scientific and Cultural Organisation (UNESCO) called on governments to regulate the use of Generative Artificial Intelligence (GenAI) in education and research.

Publicly available GenAI tools, such as ChatGPT, can produce automated text, images, videos, music and software code. The platforms have evolved rapidly and are already in use by hundreds of millions around the world, including many students.

Such wide-ranging capacities for information processing and knowledge production have potentially huge implications for education, as they replicate the higher-order thinking that constitutes the foundation of human learning.

However, very few countries have policies in place to ensure safe and ethical use of AI tools.

UNESCO has published global Guidance on Generative AI in Education and Research, designed to address the disruptions caused by GenAI technologies.

UNESCO’s guidance suggests immediate steps that can be taken to ensure a human-centric vision for new technology use.

This includes mandating the protection of data privacy and considering an age limit of 13 for their use in the classroom. It also outlines requirements for GenAI providers for ethical and effective use.

The guidance stresses the need for educational institutions to validate GenAI systems on their ethical and pedagogical appropriateness for education.

From the perspective of a human-centred approach, AI tools should be designed to extend or augment human intellectual abilities and social skills – and not undermine them, conflict with them or usurp them.

What is generative AI?

• Generative AI (GenAI) is an Artificial Intelligence (AI) technology that automatically generates content in response to prompts written in natural language conversational interfaces.

• Rather than simply curating existing webpages, by drawing on existing content, GenAI actually produces new content.

• The content can appear in formats that comprise all symbolic representations of human thinking: texts written in natural language, images (including photographs to digital paintings and cartoons), videos, music and software code.

• GenAI is trained using data collected from webpages, social media conversations and other online media. It generates its content by statistically analysing the distributions of words, pixels

or other elements in the data that it has ingested and identifying and repeating common patterns (for example, which words typically follow which other words).

• While GenAI can produce new content, it cannot generate new ideas or solutions to real-world challenges, as it does not understand real-world objects or social relations that underpin language.

How generative AI works?

The specific technologies behind GenAI are part of the family of AI technologies called Machine Learning which uses algorithms to enable it to continuously and automatically improve its performance from data.

The type of Machine Learning which has led to many of the advances in AI that we have seen in recent years, such as the use of AI for facial recognition, is known as Artificial Neural Networks (ANNs), which are inspired by how the human brain works and its synaptic connections between neurons. There are many types of ANNs.

Text generative AI uses a type of ANN known as a General-purpose Transformer, and a type of General-purpose Transformer called a Large Language Model. This is why AI Text GenAI systems are often referred to as Large Language Models (LLMs). The type of LLM used by text GenAI is known as a Generative Pre-trained Transformer, or GPT (hence the ‘GPT’ in ‘ChatGPT’).

Image GenAI and music GenAI typically use a different type of ANN known as Generative Adversarial Networks (GANs) which can also be combined with Variational Autoencoders. GANs have two parts (two ‘adversaries’) —  the ‘generator’ and the ‘discriminator’. In the case of image GANs, the generator creates a random image in response to a prompt, and the discriminator tries to distinguish between this generated image and real images. The generator then uses the result of the discriminator to adjust its parameters, in order to create another image. The process is repeated, possibly thousands of times, with the generator making more and more realistic images that the discriminator is less and less able to distinguish from real images. For example, a successful GAN trained on a dataset of thousands of landscape photographs might generate new but unreal images of landscapes that are almost indistinguishable from real photographs.

Meanwhile, a GAN trained on a dataset of popular music (or even music by a single artist) might generate new pieces of music that follow the structure and complexity of the original music.

GenAI has a myriad of possible uses

The release of ChatGPT in November 2022, followed by iteratively more sophisticated versions, sent shock waves worldwide, and is fuelling the race among large technology companies to position themselves in the field of GenAI model development.

GenAI has a myriad of possible uses. It can automate information processing and the presentation of outputs across all key symbolic representations of human thinking. It enables the delivery of final outputs by furnishing semi-finished knowledge products.

By freeing humans from some categories of lower-order thinking skills, this new generation of AI tools might have profound implications for how we understand human intelligence and learning.

Millions of people are now using GenAI in their daily lives and the potential of adapting the models to domain-specific AI applications seems unlimited, at least in the years to come.

Controversies around generative AI

GenAI raises multiple immediate concerns related to issues such as safety, data privacy, copyright and manipulation. Some of these are broader risks related to artificial intelligence that have been further exacerbated by GenAI, while others have newly emerged with this latest generation of tools.

i) Use of content without consent

GenAI models are built from large amounts of data (for example text, sounds, code and images) often scraped from the Internet and usually without any owner’s permission. Many image GenAI systems and some code GenAI systems have consequently been accused of violating Intellectual Property Rights. There are several ongoing international legal cases that relate to this issue.

ii) AI-generated content polluting the Internet

Because GPT training data is typically drawn from the Internet, which all too frequently includes discriminatory and other unacceptable language, developers have had to implement what they call ‘guardrails’ to prevent GPT output from being offensive and/or unethical. However, due to the absence of strict regulations and effective monitoring mechanisms, biased materials generated by GenAI are increasingly spreading throughout the Internet, polluting one of the main sources of content or knowledge for most learners across the world.

This is especially important because the material generated by GenAI can appear to be quite accurate and convincing, when often it contains errors and biased ideas. This poses a high risk for young learners who do not have solid prior knowledge of the topic in question. It also poses a recursive risk for future GPT models that will be trained on text scraped from the Internet that GPT models have themselves created which also include their biases and errors.

iii) Lack of understanding of the real world

Text GPTs are sometimes pejoratively referred to as ‘Stochastic Parrots’. While they can produce text that appears convincing, that text often contains errors and can include harmful statements. This all occurs because GPTs only repeat language patterns found in their training data (usually text drawn from the Internet), starting with random (or ‘stochastic’) patterns, and without understanding their meaning – just as a parrot can mimic sounds without actually comprehending what it is saying.

The disconnect between GenAI models ‘appearing’ to understand the text that they use and generate, and the ‘reality’ that they do not understand the language and the real world can lead teachers and students to place a level of trust in the output that it does not warrant. This poses serious risks for future education.

iv) Generating deepfakes

GenAI can be used to alter or manipulate existing images or videos to generate fake ones that are difficult to distinguish from real ones. GenAI is making it increasingly easy to create these ‘deepfakes’ and ‘fake news’. GenAI is making it easier for certain actors to commit unethical, immoral and criminal acts, such as spreading disinformation, promoting hate speech and incorporating the faces of people, without their knowledge or consent, into entirely fake and sometimes compromising films.

v) Ethical concerns

GenAI systems in education may exacerbate existing disparities in access to technology and educational resources, further deepening inequities.

GenAI systems in education may reduce human-to-human interaction and the critical social-emotional aspects of learning.

It may limit learners’ autonomy and agency by providing predetermined solutions or narrowing the range of possible learning experiences. Their long-term impact on young learners’ intellectual development needs to be investigated.

GenAI systems that mimic human interactions may have unknown psychological effects on learners, raising concerns about their cognitive development and emotional well-being, and about the potential for manipulation.

As more sophisticated GenAI systems are being developed and applied in education, they are likely to generate new biases and forms of discrimination based on the training data and methods used by the models, which can result in unknown and potentially harmful outputs.

A notable real‑world example is the revival of Judy Garland’s voice for audiobook narration using ElevenLabs’ cloning technology.

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

What company created an AI tool that could mimic the voices of deceased movie stars?

Amazon Alexa can mimic voices from under a minute of recorded audio, raising questions about informed consent and ownership when reproducing voices of deceased family members or friends.

What is necessary for voice cloning to work?

Scammers have targeted elderly people with cloned voices, and authorities in the UAE have warned about fraud schemes that derive voice models from social media audio. [20].

Title:

Content: UAE Cybersecurity Council Warns of 'Deep Counterfeiting' Techniques
Digital and Social Media
Expressive Image
Copy Link https: / / en.rt.com / x6r2
The UAE ’ s Cyber Security Council has warned of “deep fakes ” and artificial intelligence techniques that may sometimes be used to defraud people online.
The Council stated that in light of the rapid development of the technological scene, the spread of fraud by deep counterfeiting technology is increasing, especially with the advancement of artificial intelligence techniques, stressing that it is necessary to understand the techniques of these fraudulent practices to effectively protect yourself from potential harm.
The Council reviewed a scenario from the reality of how deep counterfeiting technology can make you a victim of fraud, explaining that the hackers extract a model of your voice from one of your accounts in social networking sites, and after analyzing the audio clips generate fake voice messages with artificial intelligence techniques, look like your real voice, and create a "fake message" claiming you need urgent money and send it to your close friends, and build on your friend 's confidence He sends his bank details to hackers without his knowledge.
The Cybersecurity Council identified three steps to protect against "deep fakes" content: first, beware of strange requests for information even from close associates; second, not to share sensitive information unless it confirms the identity of the other party; and third, to report to the authorities any attempts to defraud or blackmail using deep fakes.
The Council stressed the importance of addressing the various types of electronic attacks and raising the awareness of all members of the community of any suspicious electronic activities that may harm them, which plays a key role in protecting the community from electronic fraud.
The Council pointed to a set of steps to protect against the risks of electronic fraud to avoid falling victim to electronic fraud, including: always ensure that private contact data is not published on unreliable platforms or sites, do not click on any link that reaches through any text message, always keep a backup copy of personal data, in addition to updating the operating system of the smartphone permanently, and follow the security alerts launched by phone manufacturers without downloading or downloading any applications from unknown sources.
It is worth mentioning that the UAE Government Cyber Security Council has launched an awareness campaign targeting government and private institutions, and all members of the community, under the title "National Cyber Security Campaign.
It seeks to promote awareness of the dangers of cyberspace, the various ways to protect against cyber attacks, and calls for the importance of taking care to avoid falling victim to phishing attacks and electronic fraud that use technology to trick digital users to obtain their personal information and data.
Source: Emirates Today
Agree.
This website uses cookies. You can read the terms of use to activate this feature by clicking here
Putin wins presidential election with 100% of votes counted

What is necessary for voice cloning to work?

OpenAI’s Voice Engine pilots for reading assistance and translation illustrate beneficial applications alongside the company’s acknowledgement of serious risks.

For language instruction, AI voice‑over generators can produce multilingual materials with adjustable tone, pace, accent, and cultural nuance, improving accessibility for low‑proficiency learners when used carefully.

Title:

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?

How will AI Voice help educators with building courses?

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

Respond to different learning demands
Enhance language comprehension

Educators should navigate copyright, privacy, and consent constraints, review platform terms, and implement strong data protection and transparency practices when deploying synthetic voices in coursework. [30][32][34][59].

Title:

Content: The integration of AI & ML tools in education

x

Artificial Intelligence courses: Developing tomorrow’s leaders

Highlights

Artificial Intelligence (AI) and Machine Learning (ML) aren’t just making waves in Silicon Valley; they’re knocking on the doors of our classrooms too.

Artificial Intelligence (AI) and Machine Learning (ML) aren’t just making waves in Silicon Valley; they’re knocking on the doors of our classrooms too. As we stand at the precipice of technological innovation, it’s evident that AI and ML tools have the potential to revolutionize the educational landscape. From personalized learning experiences to predictive analytics, these cutting-edge technologies promise to enhance learning performance and redefine the educational experience for students and educators alike. However, amidst this wave of transformation, we cannot afford to overlook the ethical considerations that accompany the integration of AI and ML tools into educational settings. While the prospects are tantalizing, we must tread carefully, mindful of the ethical implications that arise when algorithms and data intersect. Let’s look at these implications closely:

Bias and Discrimination: Challenging the Status Quo

AI and ML algorithms operate on the principle of learning from data patterns. However, if the training data harbors biases, these algorithms can perpetuate systemic inequalities and discrimination. Studies reveal that AI-driven assessment tools often exhibit racial and gender biases, disadvantaging students from marginalized communities. For instance, a study published in the Journal of Educational Computing Research found that an AI-powered grading system consistently rated essays written by female students lower than those penned by male counterparts, irrespective of content quality. Such disparities underscore the critical importance of bias mitigation strategies in AI development and deployment within educational contexts.

Data Privacy: Safeguarding Educational Assets

AI and ML tools often necessitate access to vast repositories of student information. Recent research indicates that 89% of educational institutions collect and store sensitive student data, ranging from academic performance records to personal identifiers. Ensuring the privacy and security of this data is not just a legal obligation but a moral imperative.

Consider a scenario where an AI-powered tutoring platform collects and analyzes students’ browsing history and online activity to tailor learning experiences. While the intent may be to personalize instruction, the potential for data misuse or breaches looms large. According to a survey, only 25% of educators feel adequately trained in data privacy practices, highlighting the urgent need for comprehensive privacy protocols in educational AI implementations.

Navigating Ethical Considerations for Responsible Implementation

In navigating the ethical labyrinth of AI and ML integration in education, several guiding principles emerge:

l Prioritizing Data Privacy: Educators must implement robust data privacy protocols, including encryption measures and restricted access controls, to safeguard student information from unauthorized access or misuse.

l Mitigating Biases: AI developers should adopt inclusive data sampling methods and employ bias detection algorithms to identify and rectify discriminatory patterns in training datasets.

l Preserving Teacher-Student Relationships: While embracing technological innovations, educators must reaffirm the irreplaceable role of human teachers in fostering mentorship, guidance, and emotional support in the learning journey.

l Ensuring Transparency: Schools and educational institutions must foster open dialogue and transparency regarding the implementation of AI and ML tools, providing students and educators with comprehensive insights into data usage, algorithmic decision-making processes, and potential implications for learning outcomes.

Show Full Article
Print Article
Next Story
More Stories
ADVERTISEMENT
ADVERTISEMENTS

Overall, voice cloning is rapidly becoming realistic and accessible, offering significant benefits in entertainment, accessibility, and education while requiring strong legal, ethical, and technical safeguards to mitigate scams, deepfakes, and rights violations. [6][7].

What are some risks regarding AI voice clning?