Meta's new AI model can translate speech from more than 100 languages

"Meta has done a great job having a breadth of different things they support, like text-to-speech, speech-to-text, even automatic speech recognition," says Chetan Jaiswal, a professor of computer science at Quinnipiac University, who was not involved in the research. "The mere number of languages they are supporting is a tremendous achievement." Human translators are still a vital part of the translation process, the researchers say in the paper, because they can grapple with diverse cultural contexts and make sure the same meaning is conveyed from one language into another. This step is important, says Lynne Bowker, Canada Research Chair in Translation, Technologies and Society at Université Laval in Quebec, who didn't work on Seamless. "Languages are a reflection of cultures, and cultures have their own ways of knowing things," she says.