A three-week-old artificial-intelligence model called Jev has set Silicon Valley circles abuzz with discussions around alternatives to large language models, and is already sparking copycats.
Multilingual self-supervised speech models can benefit from sharing information across languages, but under a matched total pretraining data budget they still fall short of monolingual models. We show that strengthening the model’s ability to discriminate languages during pretraining reduces and, on some measures, closes this multilingual gap on continuous phonetic and higher-level linguistic measures, while…