Meta Releases AI Model That Can Transcribe And Translate Close To 100 languages

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In its quest to develop AI that can understand a range of different dialects, Meta has created an AI model, SeamlessM4T, that can translate and transcribe close to 100 languages across text and speech. Available in open source along with SeamlessAlign, a new translation dataset, Meta claims that SeamlessM4T represents a “significant breakthrough” in the field of AI-powered speech-to-speech and speech-to-text.

“Our single model provides on-demand translations that enable people who speak different languages to communicate more effectively,” Meta writes in a blog post. “SeamlessM4T implicitly recognizes the source languages without the need for a separate language identification model.”

SeamlessM4T is something of a successor to Meta’s No Language Left Behind; a text-to-text machine translation model, and Universal Speech Translator, one of the few direct speech-to-speech translation systems to support the Hokkien language. And it builds on Massively Multilingual Speech; Meta’s framework that provides speech recognition, language identification and speech synthesis tech across more than 1,100 languages.

Meta is not the only one investing resources in developing sophisticated AI translation and transcription tools. Beyond the wealth of commercial services and open source models already available from Amazon, Microsoft, OpenAI and a number of startups, Google is creating what it calls the Universal Speech Model; a part of the tech giant’s larger effort to build a model that can understand the world’s 1,000 most-spoken languages.

Mozilla, meanwhile, spearheaded Common Voice; one of the largest multi-language collections of voices for training automatic speech recognition algorithms. But SeamlessM4T is among the more ambitious efforts to date to combine translation and transcription capabilities into a single model.

 

 

 

 

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