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

## TL;DR

MaSS is a large, high-quality multilingual speech dataset derived from Bible readings, enabling research in speech alignment and translation across eight diverse languages.

## Contribution

The paper introduces MaSS, a novel multilingual corpus of sentence-aligned spoken utterances from the Bible, linking speech segments across eight languages for the first time.

## Key findings

- The corpus contains 8,130 parallel utterances across 8 languages.
- Human evaluation confirms high quality of the dataset.
- MaSS improves speech retrieval tasks with multilingual data.

## 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.