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    Home » Meta’s new AI models can recognize and produce speech for more than 1,000 languages
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    Meta’s new AI models can recognize and produce speech for more than 1,000 languages

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    Meta’s new AI models can recognize and produce speech for more than 1,000 languages
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    They skilled it on two new information units: one which incorporates audio recordings of the New Testament Bible and its corresponding textual content taken from the web in 1,107 languages, and one other containing unlabeled New Testament audio recordings in 3,809 languages. The workforce processed the speech audio and the textual content information to enhance its high quality earlier than operating an algorithm designed to align audio recordings with accompanying textual content. They then repeated this course of with a second algorithm skilled on the newly aligned information. With this methodology, the researchers had been in a position to train the algorithm to study a new language more simply, even with out the accompanying textual content.

    “We can use what that model learned to then quickly build speech systems with very, very little data,” says Michael Auli, a analysis scientist at Meta who labored on the challenge.

    “For English, we have lots and lots of good data sets, and we have that for a few more languages, but we just don’t have that for languages that are spoken by, say, 1,000 people.” 

    The researchers say their models can converse in over 1,000 languages however recognize more than 4,000. 

    They in contrast the models with these from rival firms, together with OpenAI Whisper, and declare theirs had half the error fee, regardless of masking 11 occasions more languages.

    However, the workforce warns the mannequin continues to be susceptible to mistranscribing sure phrases or phrases, which may lead to inaccurate or probably offensive labels. They additionally acknowledge that their speech recognition models yielded more biased phrases than different models, albeit solely 0.7% more. 

    While the scope of the analysis is spectacular, using non secular texts to coach AI models can be controversial, says Chris Emezue, a researcher at Masakhane, a company engaged on natural-language processing for African languages, who was not concerned within the challenge.

    “The Bible has a lot of bias and misrepresentations,” he says.

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