Language Discrimination Improves Linguistic Learning in Multilingual Speech Models

这条英文动态主要涉及模型能力与工程。原文要点：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 preservi...