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LibriS2S: A German-English Speech-to-Speech Translation Corpus

Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)

DOI:10.63317/2i6knno6666r

Abstract

Recently, we have seen an increasing interest in the area of speech-to-text translation. This has led to astonishing improvements in this area. In contrast, the activities in the area of speech-to-speech translation is still limited, although it is essential to overcome the language barrier. We believe that one of the limiting factors is the availability of appropriate training data. We address this issue by creating LibriS2S, to our knowledge the first publicly available speech-to-speech training corpus between German and English. For this corpus, we used independently created audio for German and English leading to an unbiased pronunciation of the text in both languages. This allows the creation of a new text-to-speech and speech-to-speech translation model that directly learns to generate the speech signal based on the pronunciation of the source language. Using this created corpus, we propose Text-to-Speech models based on the example of the recently proposed FastSpeech 2 model that integrates source language information. We do this by adapting the model to take information such as the pitch, energy or transcript from the source speech as additional input.

Details

Paper ID
lrec2022-main-098
Pages
pp. 928-935
BibKey
jeuris-niehues-2022-libris2s
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
79-10-95546-38-2
Conference
Thirteenth Language Resources and Evaluation Conference
Location
Marseille, France
Date
20 June 2022 25 June 2022

Authors

  • PJ

    Pedro Jeuris

  • JN

    Jan Niehues

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