Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation
Ali Can Kocabiyikoglu, Laurent Besacier, Olivier Kraif

TL;DR
This paper introduces a new 236-hour parallel speech translation corpus by aligning LibriSpeech with French translations, facilitating end-to-end speech translation research.
Contribution
It creates and releases a large, open-source parallel speech-text corpus for French-English translation based on LibriSpeech and French e-books, filling a significant resource gap.
Findings
Automatic alignment scores correlate with human judgments.
The corpus is suitable for direct speech translation experiments.
Manual evaluation confirms alignment quality.
Abstract
Recent works in spoken language translation (SLT) have attempted to build end-to-end speech-to-text translation without using source language transcription during learning or decoding. However, while large quantities of parallel texts (such as Europarl, OpenSubtitles) are available for training machine translation systems, there are no large (100h) and open source parallel corpora that include speech in a source language aligned to text in a target language. This paper tries to fill this gap by augmenting an existing (monolingual) corpus: LibriSpeech. This corpus, used for automatic speech recognition, is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. After gathering French e-books corresponding to the English audio-books from LibriSpeech, we align speech segments at the sentence level with their respective translations and obtain…
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Taxonomy
TopicsNatural Language Processing Techniques · Speech Recognition and Synthesis · Topic Modeling
