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arxiv: 2203.10752 · v3 · pith:RC2VCJ5P · submitted 2022-03-21 · cs.CL

XTREME-S: Evaluating Cross-lingual Speech Representations

Alexis Conneau , Ankur Bapna , Yu Zhang , Min Ma , Patrick von Platen , Anton Lozhkov , Colin Cherry , Ye Jia
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Clara Rivera Mihir Kale Daan Van Esch Vera Axelrod Simran Khanuja Jonathan H. Clark Orhan Firat Michael Auli Sebastian Ruder Jason Riesa Melvin Johnson
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classification cs.CL
keywords speechxtreme-sbenchmarkfamiliescross-lingualdatasetslanguagesrepresentation
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We introduce XTREME-S, a new benchmark to evaluate universal cross-lingual speech representations in many languages. XTREME-S covers four task families: speech recognition, classification, speech-to-text translation and retrieval. Covering 102 languages from 10+ language families, 3 different domains and 4 task families, XTREME-S aims to simplify multilingual speech representation evaluation, as well as catalyze research in "universal" speech representation learning. This paper describes the new benchmark and establishes the first speech-only and speech-text baselines using XLS-R and mSLAM on all downstream tasks. We motivate the design choices and detail how to use the benchmark. Datasets and fine-tuning scripts are made easily accessible at https://hf.co/datasets/google/xtreme_s.

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Cited by 2 Pith papers

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