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Automatic Speech Recognition and Query By Example for Creole Languages Documentation

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.
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Contributor : Cécile Macaire Connect in order to contact the contributor
Submitted on : Wednesday, March 30, 2022 - 5:49:50 PM
Last modification on : Thursday, May 12, 2022 - 6:08:22 PM


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  • HAL Id : hal-03625303, version 1


Cécile Macaire, Didier Schwab, Benjamin Lecouteux, Emmanuel Schang. Automatic Speech Recognition and Query By Example for Creole Languages Documentation. Findings of the Association for Computational Linguistics: ACL 2022, May 2022, Dublin, Ireland. ⟨hal-03625303⟩



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