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        <title>Automatic Speech Recognition and Query By Example for Creole Languages Documentation</title>
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        <namePart type="given">Cécile</namePart>
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        <namePart type="given">Emmanuel</namePart>
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    <abstract>We investigate the exploitation of self-supervised models for two Creole languages with few resources: Gwadloupéyen and Morisien. Automatic language processing tools are almost non-existent for these two languages. We propose to use about one hour of annotated data to design an automatic speech recognition system for each language. We evaluate how much data is needed to obtain a query-by-example system that is usable by linguists. Moreover, our experiments show that multilingual self-supervised models are not necessarily the most efficient for Creole languages.</abstract>
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    <identifier type="doi">10.18653/v1/2022.findings-acl.197</identifier>
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%0 Conference Proceedings
%T Automatic Speech Recognition and Query By Example for Creole Languages Documentation
%A Macaire, Cécile
%A Schwab, Didier
%A Lecouteux, Benjamin
%A Schang, Emmanuel
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Findings of the Association for Computational Linguistics: ACL 2022
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F macaire-etal-2022-automatic
%X We investigate the exploitation of self-supervised models for two Creole languages with few resources: Gwadloupéyen and Morisien. Automatic language processing tools are almost non-existent for these two languages. We propose to use about one hour of annotated data to design an automatic speech recognition system for each language. We evaluate how much data is needed to obtain a query-by-example system that is usable by linguists. Moreover, our experiments show that multilingual self-supervised models are not necessarily the most efficient for Creole languages.
%R 10.18653/v1/2022.findings-acl.197
%U https://aclanthology.org/2022.findings-acl.197
%U https://doi.org/10.18653/v1/2022.findings-acl.197
%P 2512-2520

Markdown (Informal)

[Automatic Speech Recognition and Query By Example for Creole Languages Documentation](https://aclanthology.org/2022.findings-acl.197) (Macaire et al., Findings 2022)

• Automatic Speech Recognition and Query By Example for Creole Languages Documentation (Macaire et al., Findings 2022)

ACL

• Cécile Macaire, Didier Schwab, Benjamin Lecouteux, and Emmanuel Schang. 2022. Automatic Speech Recognition and Query By Example for Creole Languages Documentation. In Findings of the Association for Computational Linguistics: ACL 2022, pages 2512–2520, Dublin, Ireland. Association for Computational Linguistics.