SpeechMatrix: A Large-Scale Mined Corpus of Multilingual Speech-to-Speech Translations

• URL: http://arxiv.org/abs/2211.04508v1
• Date: Tue, 8 Nov 2022 19:09:27 GMT
• Title: SpeechMatrix: A Large-Scale Mined Corpus of Multilingual Speech-to-Speech Translations
• Authors: Paul-Ambroise Duquenne, Hongyu Gong, Ning Dong, Jingfei Du, Ann Lee, Vedanuj Goswani, Changhan Wang, Juan Pino, Beno\^it Sagot, Holger Schwenk
• Abstract summary: SpeechMatrix is a large-scale multilingual corpus of speech-to-speech translations. It contains speech alignments in 136 language pairs with a total of 418 thousand hours of speech.
• Score: 38.058120432870126
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present SpeechMatrix, a large-scale multilingual corpus of speech-to-speech translations mined from real speech of European Parliament recordings. It contains speech alignments in 136 language pairs with a total of 418 thousand hours of speech. To evaluate the quality of this parallel speech, we train bilingual speech-to-speech translation models on mined data only and establish extensive baseline results on EuroParl-ST, VoxPopuli and FLEURS test sets. Enabled by the multilinguality of SpeechMatrix, we also explore multilingual speech-to-speech translation, a topic which was addressed by few other works. We also demonstrate that model pre-training and sparse scaling using Mixture-of-Experts bring large gains to translation performance. The mined data and models are freely available.

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