Research on Speech-to-Speech Translation is Booming
In just three months, universities and tech companies released over two dozen papers on speech-to-speech translation (S2ST), highlighting continuing trends, new directions in research.
Language Industry (Artificial) Intelligence — Slator Answers
In just three months, universities and tech companies released over two dozen papers on speech-to-speech translation (S2ST), highlighting continuing trends, new directions in research.
Researchers from Meta suggest training-data curation as a means to reduce added toxicity in machine translation. Toxicity categories include profanity, insults, hate speech, bullying, etc.
Interpreters pushback on RSI, Meta’s MT “breakthrough,” growth in media localization with ZOO and Keywords, Zoom’s translation feature, and Disney experiments with synthesized voices.
The new model, praised by Meta founder and CEO Mark Zuckerberg, is already being used to improve more than 25 billion translations daily on Facebook, Instagram, and other apps.
Meta eliminates text generation in speech to speech translation; shares code and research with the public.
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