Voice cloning is a technology that leverages machine learning, neural networks, and advanced natural language processing to simulate a person’s voice.

Traditionally, creating a synthetic voice required significant technical expertise and large datasets.

However, rapid advances in deep learning have made highly realistic voice cloning accessible to non-experts through a range of online tools and commercial offerings.

Modern voice cloning systems can capture and reproduce key vocal features—such as pitch, speed, rhythm, and accent—from as little as a few seconds of audio.

These systems not only convert written text into the target voice but can also convincingly replicate nuanced elements like breathing, pauses, and mouth movements, resulting in output that can be indistinguishable from real human speech .

The core technology behind voice cloning involves training neural network models on large corpora of voice data, often encompassing thousands of hours of recorded speech.

Companies and open-source projects such as Elevenlabs and Tortoise have made significant progress by developing models capable of replicating not just verbal content but also the emotional tone and expressiveness of the source speaker.

This revolution in synthetic speech generation means that AI can now learn not just what to say, but how to say it, producing outputs that can fool both humans and traditional voice recognition systems .

Voice cloning is deployed across diverse domains.

In entertainment, the technology enables deepfake videos, realistic dubbing of films and games, and audiobook narration in the distinct style and emotion of an original actor or narrator.

For example, companies like Deepdub deploy AI to synthesize actors' voices in different languages, allowing for accurate and emotive dubbing at lower costs and increased speed.

In the sphere of education and accessibility, AI voice cloning enables the creation of virtual teaching assistants, audiobooks in multiple languages or regional accents, and personalized synthetic voices for users with special needs.

Technology providers such as NeuralSpace supply voice models in many languages and dialects to deliver authentic, culturally-relevant experiences and support voice-enabled educational applications .

There are clear opportunities for language education, particularly in generating authentic listening comprehension materials for lower proficiency levels.

Tools allow instructors to script and synthesize audio in a range of dialects and accents, potentially addressing gaps in available educational resources.

The technology also supports learners by presenting content tailored to their linguistic background, pacing, or disabilities, opening new modes of language exposure.

In customer service and accessibility, AI-generated voices can engage users in their local dialect, transcribe and translate spoken content, and provide speech interfaces for people with disabilities .

Despite these benefits, current AI-generated accents and dialects present pedagogical challenges.

While tools can simulate a variety of accents and regional speech patterns, they often rely on training data that is limited or uneven across dialects.

As a result, generated accents may be inauthentic, exaggerated, or inconsistent with natural use in real communities.

Pedagogically, this can introduce inaccurate pronunciation or unintentionally reinforce stereotypes, limiting the utility of synthesized voices for learners aiming to understand natural speech as used by native speakers.

Instructors should review generated materials for quality and appropriateness and remain aware that some linguistic variations may not be faithfully reproduced by current systems.

However, the wide availability and realism of voice cloning carry significant risks.

The same features that make the technology useful for accessibility and entertainment also enable its use for malicious purposes.

Criminals can create highly convincing voice clones using only brief audio samples—sometimes as little as 20 seconds—obtained from phone calls, social media, public speeches, or other sources.

In a growing number of reported scams, perpetrators use cloned voices to impersonate relatives or trusted figures during calls, persuading victims to transfer money or provide sensitive information.

Law enforcement agencies have issued warnings about this escalating threat, highlighting the need for greater public awareness and the urgency of new prevention strategies .

High-profile incidents underscore both the promise and peril of this technology.

One widely publicized controversy involved OpenAI deploying a chatbot voice that many believed was deliberately designed to mimic actress Scarlett Johansson, allegedly without her clear consent, sparking debate about ethical boundaries and the rights of individuals over their vocal likeness.

Similarly, Elevenlabs faced backlash when its platform was used to generate offensive or unauthorized speech attributed to celebrities, fueling concerns about deepfake abuse for pranks, defamation, or more nefarious ends .

These cases reveal both technical and governance gaps regarding whose voices may be replicated, under what circumstances, and with what controls in place.

Legal frameworks concerning AI voice cloning are evolving rapidly but remain inconsistent across jurisdictions.

In the United States, legal concerns have centered on issues such as the right of publicity (protecting a person’s voice and likeness from unauthorized commercial use), enshrined in state laws such as California Civil Code § 3344 and New York’s post-mortem right of publicity statutes.

Additionally, some states have begun enacting laws targeting malicious deepfakes in election campaigns or non-consensual voice impersonation.

At the federal level, there are proposals such as the DEEPFAKES Accountability Act, but comprehensive regulation is still under development.

In the European Union, the General Data Protection Regulation (GDPR) is the principal regulation, treating voice data as personal data and requiring explicit, informed consent for the collection and processing of biometric or identity-linked information.

The proposed AI Act aims to further regulate high-risk AI applications, including synthetic voice, with obligations for transparency and risk management.

Despite these measures, gaps remain regarding the harmonization of consent standards, cross-border enforcement, and clear remedies for affected individuals .

The ethical challenges associated with voice cloning are multifaceted.

Issues include the risk of identity theft, reputational harm, and loss of control over personal identity.

The technology’s accessibility means not only celebrities but ordinary individuals are vulnerable to voice cloning from short audio samples scraped from online or recorded conversations.

Bias in voice datasets is another concern: models built using underrepresented dialects, accents, or marginalized speakers may perform less accurately, perpetuating or amplifying linguistic inequities in AI-driven applications .

Steps to mitigate harm are actively being developed.

These include tools for detecting synthetic speech, implementing voice biometric authentication, and building robust consent mechanisms into both data collection and synthesis platforms.

Organizations may also invest in watermarking generated audio to help distinguish real from synthetic speech, or in oversight processes for approving uses of sensitive voice data.

Yet, given the decentralized and open-source nature of some AI voice cloning technology, complete prevention of misuse remains challenging .

In educational applications, expert commentary highlights both exemplary use and potential pitfalls.

AI voice cloning can help bridge gaps where authentic native-speaker listening material is scarce, especially at beginner proficiency levels, and can be adjusted for regional variety to match target learner populations .

At the same time, ethical deployment demands transparency with students regarding the synthetic nature of materials, explicit permission if real individuals’ voices are used for training, and careful curation to avoid reinforcing linguistic biases or inadvertently exposing students to non-consensual or harmful content.

In summary, voice cloning technology stands at the nexus of rapid technical progress, broad applications, and pressing ethical and legal questions.

Its ability to generate realistic synthetic voices drives innovation in entertainment, education, and accessibility but also creates opportunities for fraud, misinformation, and new forms of identity misappropriation.

Real-world incidents and legal disputes stress the importance of informed consent, stronger regulation, transparency, and ongoing vigilance to balance these complex opportunities and risks.

For language educators, AI voice cloning offers substantial new possibilities for personalized, authentic listening comprehension materials, provided appropriate safeguards and ethical best practices are diligently applied .

For educators using AI voice cloning, recommended best practices include: obtaining clear consent for any real voices used, transparently informing students when materials are AI-generated, and reviewing synthetic outputs for linguistic authenticity and potential bias.

Additionally, materials should be supplementary to authentic human speech, with careful attention to the limits of AI-generated accents and dialects.

Staying informed about both technological advances and the evolving legal landscape will help instructors maximize the benefits of voice cloning tools while minimizing risks to learners and respecting personal and cultural rights.

Voice cloning is a technology that leverages machine learning, neural networks, and advanced natural language processing to simulate a person’s voice.

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

Traditionally, creating a synthetic voice required significant technical expertise and large datasets.

However, rapid advances in deep learning have made highly realistic voice cloning accessible to non-experts through a range of online tools and commercial offerings.

Title:

Content: MOSCOW, July 4 — PRIME.
Fraudsters have learned to use artificial intelligence to deceive citizens in telephone conversations.
What schemes are used by cyber scammers, told the Agency "Prime" head of information security Center digital experts Roskachestvo Sergey Kuzmenko.
Cloning of voice
According to the expert, in this case we are talking not so much about artificial intelligence, but about a neural network with machine learning based on artificial intelligence.
“Thanks to the available technology, hackers only need a 20-second snippet of a conversation taken from a social network to create a clone of any person ’ s voice.
The identity is so striking that even a mother will not be able to distinguish her child ’ s voice from a robot, ” the expert said.
The scheme of deception is the same: the AI calls and asks to transfer money.
Criminals make victims think that they are talking to a relative who suddenly needed money, for example, to compensate for damage as a result of an accident.
Kuzmenko advised immediately to call back his family and friends, from whom the request was received.
It is even better to come up with a code word for your own, so that you can understand: relatives call, not fraudsters.
Imitation of the image
You can fake not only the voice, but also the image.
Using a technique for synthesizing media content based on artificial intelligence, it is possible to impose fake images or videos on real ones.
The technology is called "deepfake" (from the English deepfake - "fake". - Approx. ed.).
Abroad, the attackers tried deepfakes when applying for remote work in the field of IT to gain access to databases.
However, the created video clips give their artificial pace of speech, asynchronous and unnatural emotions.
New technologies are used not only by advanced IT companies, but also by groups of fraudsters.
A wave of deepfakes has already engulfed Southeast Asia and Africa.
It will also certainly reach Russia in the near future and will work according to the scheme of calls from “relatives ”, for example, elderly people, the expert of Roskachestvo warned.
Thus, the moment is not far off when deceptions with calls from law enforcement agencies and bank employees will be fully implemented by software algorithms based on neural networks.
How to recognize deepfake:
• Unnatural facial expressions – the movements of the lips do not fall in time with the spoken words, the same expression of the eyes, no change of emotions is visible.
• Low resolution, pixelation or fuzziness of the image, especially in areas with active facial expressions - eyebrows, corners of the mouth.
• The sound is ahead of the picture or does not keep up with the movements of the character.
The neural networks themselves also help to recognize fakes.
Technologies for creating and detecting deepfakes will be intensively developed in the future.
According to Kuzmenko, for the average user, the best way to protect yourself from deepfakes is to be vigilant, turn to reliable sources of information and follow the development of information technologies.

Modern voice cloning systems can capture and reproduce key vocal features—such as pitch, speed, rhythm, and accent—from as little as a few seconds of audio.

Title:

Content: The scary side of artificial intelligence

The pros of AI outweigh the Cons or threats in our day-to-day lives, and there’s no magic pill to protect us from the scary threats of AI.

  • Exclusive

It's a free Content, simply login/signup to unlock

Get in-depth Industry Insights and Analysis through our “Exclusive” content, presented to you by our esteemed panel of writers, for free

By continuing, you agree to the Terms & Conditions and acknowledge our Privacy Policy. This same account can be used across all Economic Times B2B portals.

  • Updated On Oct 3, 2023 at 03:02 PM IST

Artificial intelligence (AI), as we all know, is the simulation of human intelligence leveraging computer systems and machines. AI programs can continuously learn and evolve with experience. In technical terms, AI systems render the output by churning and analyzing the data for correlations and patterns and help make future predictions using these patterns.

Advt
Today AI is being used extensively in all facets of our lives starting from lifestyle, e-commerce, home appliances, automobiles, navigation, transport, healthcare, agriculture, education, financial planning, chatbots, marketing, cyber security, virtual assistant, industrial automation and many more.

Clearly, we have and are leveraging the strengths of AI to the fullest to automate the routine tasks and make it auto-learn over a period. There’s no doubt that AI has revolutionized the lives of all – organizations, consumers etc. But as they say, “Everything comes at a price”. This analogy is quite true for AI as well, there have been a lot of threats that have emerged using AI and are being utilized by the Cyber criminals to dupe the ignorant users, cause mental stress and extort money.

continued below

Executive Workshop

I’m not going to delve into all of threats but would like to elucidate some of the real ones that have come to the surface recently:

Voice cloning or mimicry

As the name suggests, it uses machine learning algorithms to simulate anyone’s voice. It requires certain voice data to analyze and learn the specific patterns of any individual. There are certain advantages of cloning a voice that can be used in voice assistants, chatbots, navigation systems and other areas. Voice cloning has existed for a while but was restricted to experts who possess the technical knowledge to be able to use the same. But now AI Voice cloning tools are available on the open Internet that anyone can leverage with literally no technical knowledge or cost to clone anyone’s voice. All you need to do is just Google and it will pop up and get a bunch of both free and paid AI Voice cloning tools.

Advt
In fact, recently one of the global leaders in online protection published a report stating how AI is fueling a rise in online voice scams, with just three seconds of audio required to clone a person’s voice. This is extremely creepy. Just imagine, if a Cyber-criminal clones your voice and tricks your near ones by making them believe that they are talking to you, and request for money due to any distress reasons. In fact, these are not assumptions but real-life incidents that are happening across the world every minute.

Deepfakes AI

Deepfakes AI are being used to impersonate an individual by manipulating videos, images, audios, and other content available on the social media platforms using deep learning techniques. It mainly transforms existing content from one person to another. This is another area that has been exploited by the Cyber criminals in the recent past, and there are a few deepfake cases that have made waves on the Internet. One of the most famous ones being Deepfake created by a VFX artist of one of Hollywood’s most famous male actors. This piece was so well made by rendering thousands of pictures using artificial versions of the actor. There are similar Deepfakes incidents involving other global celebrities and leaders. The damage and misuse of the deepfakes videos could be extremely dangerous for the human society and can be used by terrorists to incite riots and create nuisance.

Creating virtual people

This is another area where AI is being used to create people that do not exist. There are a lot of websites that allow you to generate a random image by just specifying the age group, gender & ethnicity, and you can continue to refresh these images at the click of a button. Be mindful of the fact that these images pertain to people that do not exist in this world. On the similar lines, there’s an emerging trend of AI news anchors that possess a human-like appearance and are fed data that they can read using text-to-speech technology. Recently, there's been a surge of AI-Driven robotic new anchors in multiple language channels. While the main objective of this initiative is to provide royalty free or cost-effective human images for branding and other purposes. However, the overuse of these technologies causes Fear of missing out (FOMO), Feeling of inadequacy, dissatisfaction, and isolation may potentially lead to psychological and emotional vulnerabilities.

One of the Hollywood movies, ‘HER’ portrayed an introverted and lonely writer (Joaquin Phoenix) who purchases an AI virtual assistant personified through a female voice to assist him in his writing job. However, when he finds out about its ability to learn and adapt, he falls in love with it. The film delves into emotional vulnerability and the impact of AI on human relationships.

Needless to say, that the pros of AI outweigh the Cons or threats in our day-to-day lives, and there’s no magic pill to protect us from the scary threats of AI. However, there are certain preventive tips that one can follow to mitigate any such risks. Do spread awareness with your family and friends:

  • Set some code words with family, and friends to verify the identity during emergency circumstances
  • Optimize social media presence by limiting your connections with only known contacts and avoid connecting with any unknown ones
  • Avoid saying ‘Yes’ as a greeting while receiving unknown calls as it can be used to authorize credit card charges or other purposes
  • Continuously update privacy settings on social media to allow viewing by friends and family only
  • Avoid clicking on any suspicious links or calls received without proper due diligence
  • Do not share your passwords and other sensitive information with anyone
  • Verify the credentials of any online information before circulating it through various mediums
  • Avoid public Wi-Fi connections offered at coffee shops or airports, which requires to enter password
  • Closely monitor the time spent by younger generation on social media and online gaming
  • Finally, in case of any suspicion, double check and report it to the host site or concerned authorities
The author is the CIO of MOVIN

Disclaimer: The views expressed are solely of the author and ETCIO does not necessarily subscribe to it. ETCIO shall not be responsible for any damage caused to any person/organization directly or indirectly.

  • Published On Oct 3, 2023 at 03:02 PM IST

Most Read in Artificial Intelligence

Join the community of 2M+ industry professionals

Subscribe to our newsletter to get latest insights & analysis.

Download ETCIO App

  • Get Realtime updates
  • Save your favourite articles

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?

These systems not only convert written text into the target voice but can also convincingly replicate nuanced elements like breathing, pauses, and mouth movements, resulting in output that can be indistinguishable from real human speech .

Title:

Content: Expressionkaspersky.com
What are the mysteries of deep sonic falsification?
The spread of artificial intelligence and easy access to tools capable of altering the truth have led to the emergence of one of the most shocking and disturbing digital manipulation techniques, “deepfake. ”
Deep fakes make it possible to create fake videos, photos and sounds that show individuals saying or doing things they never said or did, and although the most popular version until recently was video, deep fakes are gaining importance day by day.
A historical overview
The first major program to bring the potential of deep voice counterfeiting to the general public was Adobe Voco in 2016, which used artificial intelligence to mimic a person ’ s voice from a short recording.
emoticalipwatchdog.com
The software was scrapped after it was found that it could be used to create false, misleading and dangerous sounds, and since then, advances in neural network technology have enabled increasingly realistic and convincing audio falsifications.
At present, we can find many applications and tools online that use this technology to create fake sounds, where Microsoft has launched an artificial intelligence model called VALL-E that can imitate the human voice with a recording of only three seconds.
Deep sonic falsification
Deep voice falsification aims to create an audio model capable of replicating the actual speaker ’ s voice, but the model must be trained through the speaker ’ s audio recordings, in order to be ready to generate an artificial sound similar to that of the original person.
expressiontelegraph.co.uk
Deep learning and natural language processing techniques are used to analyze the unique patterns and characteristics of sound, some of which include pitch, speed, rhythm and tone, and artificial intelligence uses recordings to deliver an original sound, creating a new audio recording that mimics the speaker ’ s voice to a full degree.
How to Create Deep Audio Counterfeiting
Fake deep voice is created using AI-powered text to speech technology, and this can be done with just a few minutes of recorded speech to train an AI speech model, which can read any text with the target voice.
expressionveritonevoice.com
The original recorded sound must be of sufficient quality to sample the unique characteristics of the speaker ’ s voice, after which AI algorithms analyze the patterns and characteristics of the original sound and learn to mimic them.
This can be done with male and female voices and adaptation to the identity of the speaker, the result is a fake voice recording that mimics the voice of the original person, and in addition to generating speech, these instruments can simulate sounds such as breathing and mouth movements.
Initiatives to combat voice counterfeiting
There are initiatives aimed at combating this increasingly prevalent voice counterfeiting, and some technologies can detect these counterfeit products, such as voice biometrics, an authentication method that uses a person ’ s unique voice pattern to verify their identity.
expressionclt.nliu.ac.in
This pattern includes characteristics such as tone and pitch of the voice, speech speed, and pronunciation, and to use voice biometrics, a person's voice must be captured, after which, its unique characteristics are analyzed as well as the length of the words.
Spectroscopy can also be used, consisting of analyzing acoustic signals to detect unique sound patterns that are difficult to replicate in deep fakes.
There are also tools that can detect the digital traces present in deep voice fakes, because the latter fails to accurately simulate all the variables of the actual voice recording, and therefore, deep fakes may contain breaks in sound or background noise that differ from those expected in the original sound.
Most Read
No stories found.
Erm News
www.eremnews.com

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

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

Difficult to distinguish from human voice

The core technology behind voice cloning involves training neural network models on large corpora of voice data, often encompassing thousands of hours of recorded speech.

What is necessary for voice cloning to work?

Companies and open-source projects such as Elevenlabs and Tortoise have made significant progress by developing models capable of replicating not just verbal content but also the emotional tone and expressiveness of the source speaker.

Title:

Content: OpenAI's Johansson gaffe pushes voice cloning into spotlight

Law enforcement warned that AI clones could be used to extort money from loved ones over the phone

By AFP

  • Follow us on

Scarlett Johansson voiced an AI character in the film "Her". — Reuters file

Published: Mon 27 May 2024, 7:51 PM

Last updated: Mon 27 May 2024, 7:52 PM

OpenAI was forced to apologise to actor Scarlett Johansson last week for using her voice -- or something very similar -- on its latest chatbot, throwing the spotlight on to voice-cloning tech.

Although OpenAI denied the voice they used was Johansson's, their case was not helped by CEO Sam Altman flagging the new model with a one-word message on social media -- "Her".

Johansson voiced an AI character in the film "Her", which Altman has previously said is his favourite film about the technology.

Right from the start, AI voice cloning has proved problematic.

Last year, British firm Elevenlabs went viral for all the wrong reasons when it released its voice-cloning software.

Internet pranksters immediately began pushing out deepfaked celebrities -- Harry Potter star Emma Watson was shown reading Hitler's Mein Kampf.

Law enforcement warned that AI clones could be used to extort money from loved ones over the phone.

The technology has developed rapidly in the past year becoming far more realistic and nuanced.

Danish entrepreneur Victor Riparbelli, CEO of British AI firm Synthesia, told AFP it was largely down to a program called Tortoise that was released two years ago.

The program's developers threw thousands of hours of voice data into their model in an unstructured way and discovered it not only learnt what to say but how to say it.

"That was a pretty big paradigm shift," Riparbelli said on the sidelines of last week's VivaTech conference in Paris.

Tortoise was an open source program and Elevenlabs was the first to go to market using it.

OpenAI uses similar systems though they do not release any details.

Much of the controversy around voice cloning has focused on concerns over people misusing the software.

But the claim against OpenAI is unusual because it is the company itself accused of playing fast and loose.

"It was very unfortunate that OpenAI did that -- really not very good," Katya Laine, CEO of TALKR.ai, told AFP at VivaTech.

"If they actually cloned her voice without her knowing then I think that's very very bad," said Riparbelli.

The two entrepreneurs are among hundreds harnessing AI voice programs for uses that they argue will make companies more efficient.

Laine's firm provides virtual voice assistants -- essentially AI customer service agents.

She said her firm's system could now resolve 25 to 30 percent of calls without any human involvement.

Synthesia specialises in video avatars, which Riparbelli said allowed any office worker to turn text or slides into a video performed by a realistic AI.

Both Riparbelli and Laine allow their clients to use their own avatars, off-the-shelf products or those supplied by the likes of OpenAI and Elevenlabs.

Riparbelli said Synthesia used actors whose likenesses and voices were licensed for two years with an option to renew after the initial period.

The problems arise if actors' voices are used without their consent.

The fiasco overshadowed a developer conference in Paris last week when OpenAI was showing off a suite of new tools.

In front of a big screen in an auditorium, Romain Huet, OpenAI's Head of Developer Experience, breezily chatted into his phone.

Seconds later, his short voice sample had been processed and could be heard commentating over a generated video -- in five languages.

The demonstration showed how quickly the field is moving, but the headlines had already been written.

The Washington Post asked in a newsletter "How dumb is OpenAI?", other commentators were suggesting wunderkind Altman was nothing more than a huckster.

Nonetheless, Riparbelli was open to OpenAI's argument that they had used another actor who just sounded liked Johansson.

"If it's not her but someone who sounds a lot like her... where do you draw that line," Riparbelli asked.

"If they're not allowed to use someone who sounds a lot like her, then it sets a very odd precedent."

More news from World

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

This revolution in synthetic speech generation means that AI can now learn not just what to say, but how to say it, producing outputs that can fool both humans and traditional voice recognition systems .

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

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

Difficult to distinguish from human voice

Voice cloning is deployed across diverse domains.

In entertainment, the technology enables deepfake videos, realistic dubbing of films and games, and audiobook narration in the distinct style and emotion of an original actor or narrator.

Title:

Content: “The Deep Falsification. ”
This is how you can discover sound and image fabrication | Politics and economics | In-depth analysis with a broader perspective than DW | DW | 08.01.2022
1.
Inhalt
2.
Navigation
3.
Weitere Inhalte
4.
Metanavigation
5.
Suche
6.
Choose from 30 Languages
Announcement
Politics and Economics
"The Deep Fake."
This is how you can detect the fabrication of sound and image.
In the era of what is known as deep fakes, it has become difficult to tell whether a video is real or not with the naked eye.
But we shouldn't worry, there are ways to find out.
DW has some advice to find out.
Combining the dance, voice and image of American singer Bruno Mars I would advise an example of employing the technique of "deep fakes"
Imagine dancing and singing with the same dexterity, agility and sound power as Bruno Mars!
Many people may think that the technology used to enable anyone to do or say things they have never done is complex, and it can be easily owned, as it only takes footage and video to start creating an “alternative reality. ”
This technique of manipulating both visual and audio content using artificial intelligence is called deepfakes.
This example dates back to 2018 and is still impressive, but now thanks to the “deep fakes ” technique it can be very realistic and convincing.
What is "deep fakes"?
The term "deep fakes" accurately describes the process of collecting audio and video files by artificial intelligence or machine learning.
All areas of "deep fakes" are possible, starting from changing faces, meaning replacing one person's face with another, or synchronizing the movement of the lips, where the speaker's mouth can be set to an audio file different from the original sound or the reproduction of the sound, where a copy of the sound is reproduced for use to say other things.
It is not only at this level, but also completely artificial faces and bodies can be created, for example, a digital avatar.
What ’ s more, “deep fakes ” can be used to evoke the dead, as the Dali Museum in Florida did with Salvador Dali, where the American Museum used this technique to allow visitors to take a live photo with Dali — who died in 1989 — and take selfies himself.
The process of using artificial intelligence to manipulate a video is based on a technique known as the "generative adversarial network", which is a model of machine learning, where two neural networks compete against each other for more accurate results, as this technology aims to improve results.
We may find it difficult to understand what is meant by the competition of two networks, but we will explain how the process works: one computer will inform the other computer if the digital reproduction, whether visual or auditory, that it has made for anyone is convincing and substantially identical to that person ’ s original; that is, whether the lip movement in the cloned copy is identical to the original, and whether facial expressions are identical.
Using the "generative adversarial network", the system as a whole is optimized until a convincing result is reached.
Although this technology is constantly being developed and improved, anyone can detect manipulation whether visual or audio in other words catch “deep fakes ” if the thing we ’ re looking for is identified.
Methods of Detecting "Deep Counterfeiting"
Capturing clips that have been subjected to "deep fakes" does not require one to be an expert in this complex technique in order to distinguish what is real from what is fake.
In that, DW offers some tips to help investigate “deep fakes. ”
First watch the clip carefully and do not rush to publish it, and ask yourself the question: is this clip real?
Couldn't it have been fabricated?
If you are in doubt, do not post it or send it to anyone.
In case of doubt, you should do a search for the same story or clip from different but trustworthy sources on the Internet, as finding a similar story will help you grab the edge of the thread to get to the real story.
If you suspect an audio, image, or video clip, enter that part into Google or DuckDuckGo and look for a similar version.
The two versions can then be compared.
Detecting and detecting some of the effects of manipulation is the biggest challenge, but there are some aspects that may help, such as the presence of inconsistent footage or change in tone or quality of sound and others, no matter how small, may be useful and you have to trust your visual and auditory senses and always ask yourself: Does it make sense?
You should remember that it only takes a lot of focus and you may need to seek help from someone else to help you identify where the manipulations might be simple things like nose, ear, teeth, whiteness or even hairstyle and whether it looks the same.
It may be necessary to view the clip at a scene rate to detect inconsistencies, for example the VL Media Player.
See also watchframebyframe.com.
Also, zoom in on the movements of the mouth and lips and compare them to the original version to discover the synchronization of the movement of the lips, and whether it makes sense.
Enhance your audio-visual skills
It is clear from all the above that it is all about the human senses, especially the auditory and visual skills, and fortunately you can enhance these abilities, through this training you can improve your hearing and vision skills to detect any manipulation of the image or sound.
High risk of "deep fakes" technique
The technique of "deep fakes" can be used in the field of pornography that comes within the framework of what is known as "revenge porn", in which fake pornographic images or clips are posted in order to blackmail or even damage the reputation of the victim.
“Revenge porn ” is defined as posting mostly pornographic images or videos online with the aim of taking revenge and harming people.
As for societies in general, the dangers of deepfakes depend on how we consume the Internet: people see too much when browsing the web and social media and are not always sure what they are posting or sharing, whether it is real or fabricated.
How to Detect Misinformation and Detect Deep Counterfeiting?
In polarized societies, deep fakes are a great opportunity to trick people into believing certain things.
It is not about the quality of the fake video, it may be what you saw, even if it is not true, for example a video of former England star David Beckham speaking nine languages.
In April 2019, Beckham launched a campaign to eradicate malaria by sending a message through a video clip in nine languages.
He began the letter in English and then spoke in eight other languages, but the other eight languages were not in his own voice but in the voices of malaria survivors and doctors.
At the time, the British organisation that produced the video said it had used video technology to make Beckham appear to speak these eight languages.
Politically, a fake “deepfakes ” video was produced by De Correspondent showing Dutch Prime Minister Mark Rutte talking about a major policy change, saying he would fully support long-term climate action.
Some politicians may benefit from a media climate filled with misinformation, but the presence of technology such as "deep fakes" allows them to claim that what they have said is untrue and false and it will be difficult to prove otherwise.
Perhaps the most striking example of this is former US President Donald Trump ’ s claim in 2016 that a 2005 video in which he spoke profanely about women was fabricated, although he later apologized for those words.
Salvador Dali Museum in Florida used artificial intelligence to bring back international painter Salvador Dali "from the dead"
Lesson learned
The bottom line is that spreading misinformation can be for the most prominent reasons of arousing suspicion and controversy or supporting certain beliefs in a deceptive way, but it does make the desired noise.
It may be difficult to verify manipulated videos or audio, but one can be trained to learn how to spot “deep fakes. ”
Above all, it is necessary to stop posting or sharing anything that has not been verified as authentic.
Julia Baer, Robin Baumeister / GC

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

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

For example, companies like Deepdub deploy AI to synthesize actors' voices in different languages, allowing for accurate and emotive dubbing at lower costs and increased speed.

Title:

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

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

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

In the sphere of education and accessibility, AI voice cloning enables the creation of virtual teaching assistants, audiobooks in multiple languages or regional accents, and personalized synthetic voices for users with special needs.

How will AI Voice help educators with building courses?

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

Technology providers such as NeuralSpace supply voice models in many languages and dialects to deliver authentic, culturally-relevant experiences and support voice-enabled educational applications .

Title:

Content: There were 107 press releases posted in the last 24 hours and 446,378 in the last 365 days.
VoiceAI, technology for local dialects, transforming global customer service experiences
NeuralSpace launches AI voices in local languages
NeuralSpace logo
NeuralSpace's VoiceAI platform
LONDON, UNITED KINGDOM, December 10, 2023 / EINPresswire.com / --
NeuralSpace, a leader in linguistic artificial intelligence, has launched a transformative voice technology feature within its VoiceAI platform, offering realistic artificial sounds in Arabic, Hindi and English.
The innovation, unveiled on December 11, marks a major development in sound technology, offering speech formulation with unparalleled precision, especially in local dialects such as Saudi Arabia.
Three main advantages characterize NeuralSpace ’ s offerings:
Cultural Interaction: Artificial sounds capture the essence of local dialects, fostering deep communication between users and technology in regions such as Saudi Arabia, India and the English-speaking world.
Instantaneous Interaction: VoiceAI technology provides instantaneous, natural-sounding voice feedback, which is essential for dynamic speech generation in virtual assistants and voice response systems.
Ease of integration: The technology is sophisticated but easy to use, allowing developers to effortlessly optimize their applications.
VoiceAI for NeuralSpace meets the growing demand for accurate transcription, speech analytics and authentic synthetic sounds.
These AI sounds are finely tuned to real-world interactions, providing engaging and realistic user experiences.
Felix Le Mans, CEO and co-founder of NeuralSpace, said:
“NeuralSpace was founded with a vision to make the technology globally available in any language.
Today, with the release of our natural AI sounds, we are one step closer to turning this dream into reality.
Our human-quality Saudi, Indian and English voices in AI are not just revolutionizing technological innovation; they are gateways to make dialectical interactions with technology a tangible experience for everyone. ”
About VoiceAI: This platform and application programming interface (API) allow companies to copy, translate and analyze voice data with exceptional accuracy, especially in Arabic and Hindi.
Key features include up to 91% copy accuracy for these languages, surpassing major tech brands.
The platform also ensures high-level data security through in-house deployment, NeuralSpace ’ s ISO 27001 certification and compliance with the General Data Protection Law.
NeuralSpace invites you to integrate VoiceAI into your systems, and promises to change customer experiences.
The platform can be accessed via a code-free web platform, REST APIs, and Python SDK, ensuring easy integration.
About NeuralSpace: At the forefront of linguistic artificial intelligence, NeuralSpace is committed to technologies that enhance human-machine communication.
VoiceAI embodies this vision, reflecting the diversity and richness of human languages.
For more information, demos or enquiries, visit www.neuralspace.ai or contact sales @ neuralspace.ai.
NeuralSpace ’ s latest innovation is more than just a technological advance; it ’ s a step towards a future where you not only understand technology but also speak with a voice that resonates with the cultural richness of human languages.
Melanie Swamy-Brown
NeuralSpace
melanie @ neuralspace.ai
Visit us on social media:
Twitter
LinkedIn
Youtube

How will AI Voice help educators with building courses?

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

There are clear opportunities for language education, particularly in generating authentic listening comprehension materials for lower proficiency levels.

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

Enhance language comprehension
Respond to different learning demands

Tools allow instructors to script and synthesize audio in a range of dialects and accents, potentially addressing gaps in available educational resources.

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

Enhance language comprehension
Respond to different learning demands

The technology also supports learners by presenting content tailored to their linguistic background, pacing, or disabilities, opening new modes of language exposure.

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

Enhance language comprehension
Respond to different learning demands

In customer service and accessibility, AI-generated voices can engage users in their local dialect, transcribe and translate spoken content, and provide speech interfaces for people with disabilities .

Despite these benefits, current AI-generated accents and dialects present pedagogical challenges.

While tools can simulate a variety of accents and regional speech patterns, they often rely on training data that is limited or uneven across dialects.

What are some risks regarding AI voice clning?

As a result, generated accents may be inauthentic, exaggerated, or inconsistent with natural use in real communities.

Pedagogically, this can introduce inaccurate pronunciation or unintentionally reinforce stereotypes, limiting the utility of synthesized voices for learners aiming to understand natural speech as used by native speakers.

What are some risks regarding AI voice clning?

Instructors should review generated materials for quality and appropriateness and remain aware that some linguistic variations may not be faithfully reproduced by current systems.

However, the wide availability and realism of voice cloning carry significant risks.

What are some risks regarding AI voice clning?

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

could become a popular method of attacking banks and financial services

The same features that make the technology useful for accessibility and entertainment also enable its use for malicious purposes.

What are some risks regarding AI voice clning?

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

could become a popular method of attacking banks and financial services

Criminals can create highly convincing voice clones using only brief audio samples—sometimes as little as 20 seconds—obtained from phone calls, social media, public speeches, or other sources.

What is necessary for voice cloning to work?

In a growing number of reported scams, perpetrators use cloned voices to impersonate relatives or trusted figures during calls, persuading victims to transfer money or provide sensitive information.

Law enforcement agencies have issued warnings about this escalating threat, highlighting the need for greater public awareness and the urgency of new prevention strategies .

High-profile incidents underscore both the promise and peril of this technology.

One widely publicized controversy involved OpenAI deploying a chatbot voice that many believed was deliberately designed to mimic actress Scarlett Johansson, allegedly without her clear consent, sparking debate about ethical boundaries and the rights of individuals over their vocal likeness.

Similarly, Elevenlabs faced backlash when its platform was used to generate offensive or unauthorized speech attributed to celebrities, fueling concerns about deepfake abuse for pranks, defamation, or more nefarious ends .

What are some risks regarding AI voice clning?

These cases reveal both technical and governance gaps regarding whose voices may be replicated, under what circumstances, and with what controls in place.

What are some risks regarding AI voice clning?

Legal frameworks concerning AI voice cloning are evolving rapidly but remain inconsistent across jurisdictions.

In the United States, legal concerns have centered on issues such as the right of publicity (protecting a person’s voice and likeness from unauthorized commercial use), enshrined in state laws such as California Civil Code § 3344 and New York’s post-mortem right of publicity statutes.

Additionally, some states have begun enacting laws targeting malicious deepfakes in election campaigns or non-consensual voice impersonation.

At the federal level, there are proposals such as the DEEPFAKES Accountability Act, but comprehensive regulation is still under development.

In the European Union, the General Data Protection Regulation (GDPR) is the principal regulation, treating voice data as personal data and requiring explicit, informed consent for the collection and processing of biometric or identity-linked information.

The proposed AI Act aims to further regulate high-risk AI applications, including synthetic voice, with obligations for transparency and risk management.

Despite these measures, gaps remain regarding the harmonization of consent standards, cross-border enforcement, and clear remedies for affected individuals .

The ethical challenges associated with voice cloning are multifaceted.

Issues include the risk of identity theft, reputational harm, and loss of control over personal identity.

The technology’s accessibility means not only celebrities but ordinary individuals are vulnerable to voice cloning from short audio samples scraped from online or recorded conversations.

What is necessary for voice cloning to work?

Bias in voice datasets is another concern: models built using underrepresented dialects, accents, or marginalized speakers may perform less accurately, perpetuating or amplifying linguistic inequities in AI-driven applications .

What are some risks regarding AI voice clning?

Steps to mitigate harm are actively being developed.

These include tools for detecting synthetic speech, implementing voice biometric authentication, and building robust consent mechanisms into both data collection and synthesis platforms.

Organizations may also invest in watermarking generated audio to help distinguish real from synthetic speech, or in oversight processes for approving uses of sensitive voice data.

Yet, given the decentralized and open-source nature of some AI voice cloning technology, complete prevention of misuse remains challenging .

What are some risks regarding AI voice clning?

In educational applications, expert commentary highlights both exemplary use and potential pitfalls.

AI voice cloning can help bridge gaps where authentic native-speaker listening material is scarce, especially at beginner proficiency levels, and can be adjusted for regional variety to match target learner populations .

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

Enhance language comprehension
Respond to different learning demands

At the same time, ethical deployment demands transparency with students regarding the synthetic nature of materials, explicit permission if real individuals’ voices are used for training, and careful curation to avoid reinforcing linguistic biases or inadvertently exposing students to non-consensual or harmful content.

What are some risks regarding AI voice clning?

In summary, voice cloning technology stands at the nexus of rapid technical progress, broad applications, and pressing ethical and legal questions.

Its ability to generate realistic synthetic voices drives innovation in entertainment, education, and accessibility but also creates opportunities for fraud, misinformation, and new forms of identity misappropriation.

What are some risks regarding AI voice clning?

Real-world incidents and legal disputes stress the importance of informed consent, stronger regulation, transparency, and ongoing vigilance to balance these complex opportunities and risks.

For language educators, AI voice cloning offers substantial new possibilities for personalized, authentic listening comprehension materials, provided appropriate safeguards and ethical best practices are diligently applied .

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

For educators using AI voice cloning, recommended best practices include: obtaining clear consent for any real voices used, transparently informing students when materials are AI-generated, and reviewing synthetic outputs for linguistic authenticity and potential bias.

What are some risks regarding AI voice clning?

Additionally, materials should be supplementary to authentic human speech, with careful attention to the limits of AI-generated accents and dialects.

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

Staying informed about both technological advances and the evolving legal landscape will help instructors maximize the benefits of voice cloning tools while minimizing risks to learners and respecting personal and cultural rights.