Direct Text to Speech Translation System using Acoustic Units

This paper proposes a direct text to speech translation system using discrete acoustic units. This framework employs text in different source languages as input to generate speech in the target language without the need for text transcriptions in this language. Motivated by the success of acoustic u...

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Bibliographic Details
Published inarXiv.org
Main Authors Mingote, Victoria, Gimeno, Pablo, Vicente, Luis, Khurana, Sameer, Laurent, Antoine, Duret, Jarod
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 14.09.2023
Subjects
Algorithms
Clustering
Coders
Computer Science - Computation and Language
Computer Science - Learning
Computer Science - Sound
Encoders-Decoders
Languages
Speech encoders
Speech recognition
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Summary:This paper proposes a direct text to speech translation system using discrete acoustic units. This framework employs text in different source languages as input to generate speech in the target language without the need for text transcriptions in this language. Motivated by the success of acoustic units in previous works for direct speech to speech translation systems, we use the same pipeline to extract the acoustic units using a speech encoder combined with a clustering algorithm. Once units are obtained, an encoder-decoder architecture is trained to predict them. Then a vocoder generates speech from units. Our approach for direct text to speech translation was tested on the new CVSS corpus with two different text mBART models employed as initialisation. The systems presented report competitive performance for most of the language pairs evaluated. Besides, results show a remarkable improvement when initialising our proposed architecture with a model pre-trained with more languages.
ISSN:2331-8422
DOI:10.48550/arxiv.2309.07478