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Pré-publication, Document de travail

User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis

Abstract : This paper reports on progress integrating the speech recognition toolkit ESPnet into Elpis, a web front-end originally designed to provide access to the Kaldi automatic speech recognition toolkit. The goal of this work is to make end-to-end speech recognition models available to language workers via a user-friendly graphical interface. Encouraging results are reported on (i) development of an ESPnet recipe for use in Elpis, with preliminary results on data sets previously used for training acoustic models with the Persephone toolkit along with a new data set that had not previously been used in speech recognition, and (ii) incorporating ESPnet into Elpis along with UI enhancements and a CUDA-supported Dockerfile.
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https://halshs.archives-ouvertes.fr/halshs-03030529
Contributeur : Alexis Michaud <>
Soumis le : lundi 14 décembre 2020 - 14:04:27
Dernière modification le : jeudi 15 avril 2021 - 15:08:16
Archivage à long terme le : : lundi 15 mars 2021 - 18:04:57

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Elpis_ComputEL4.pdf
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Distributed under a Creative Commons Paternité - Pas d'utilisation commerciale - Partage selon les Conditions Initiales 4.0 International License

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  • HAL Id : halshs-03030529, version 1
  • ARXIV : 2101.03027

Citation

Oliver Adams, Benjamin Galliot, Guillaume Wisniewski, Nicholas Lambourne, Ben Foley, et al.. User-friendly automatic transcription of low-resource languages: Plugging ESPnet into Elpis. 2020. ⟨halshs-03030529v1⟩

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