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MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible

Abstract : The CMU Wilderness Multilingual Speech Dataset (Black, 2019) is a newly published multilingual speech dataset based on recorded readings of the New Testament. It provides data to build Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) models for potentially 700 languages. However, the fact that the source content (the Bible) is the same for all the languages is not exploited to date. Therefore, this article proposes to add multilingual links between speech segments in different languages, and shares a large and clean dataset of 8,130 parallel spoken utterances across 8 languages (56 language pairs). We name this corpus MaSS (Multilingual corpus of Sentence-aligned Spoken utterances). The covered languages (Basque, English, Finnish, French, Hungarian, Romanian, Russian and Spanish) allow researches on speech-to-speech alignment as well as on translation for typologically different language pairs. The quality of the final corpus is attested by human evaluation performed on a corpus subset (100 utterances, 8 language pairs). Lastly, we showcase the usefulness of the final product on a bilingual speech retrieval task.
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Submitted on : Friday, June 5, 2020 - 10:23:02 AM
Last modification on : Sunday, June 26, 2022 - 5:08:34 AM
Long-term archiving on: : Wednesday, September 23, 2020 - 9:02:24 PM


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  • HAL Id : hal-02611059, version 1
  • ARXIV : 1907.12895


Marcely Zanon Boito, William N Havard, Mahault Garnerin, Éric Le Ferrand, Laurent Besacier. MaSS: A Large and Clean Multilingual Corpus of Sentence-aligned Spoken Utterances Extracted from the Bible. Proceedings of The 12th Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.6486 - 6493. ⟨hal-02611059⟩



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