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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
Contributor : Alexis Michaud <>
Submitted on : Monday, December 14, 2020 - 2:04:27 PM
Last modification on : Monday, December 28, 2020 - 5:10:03 PM

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Elpis_ComputEL4.pdf
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Distributed under a Creative Commons Attribution - NonCommercial - ShareAlike 4.0 International License

Identifiers

  • 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-03030529⟩

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