arXiv Open Access 2021

Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning

Jama Hussein Mohamud Lloyd Acquaye Thompson Aissatou Ndoye Laurent Besacier

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Abstrak

This paper describes the results of an informal collaboration launched during the African Master of Machine Intelligence (AMMI) in June 2020. After a series of lectures and labs on speech data collection using mobile applications and on self-supervised representation learning from speech, a small group of students and the lecturer continued working on automatic speech recognition (ASR) project for three languages: Wolof, Ga, and Somali. This paper describes how data was collected and ASR systems developed with a small amount (1h) of transcribed speech as training data. In these low resource conditions, pre-training a model on large amounts of raw speech was fundamental for the efficiency of ASR systems developed.

Topik & Kata Kunci

cs.SD cs.CL eess.AS

Penulis (4)

Jama Hussein Mohamud

Lloyd Acquaye Thompson

Aissatou Ndoye

Laurent Besacier

Format Sitasi

APA MLA BibTeX

Mohamud, J.H., Thompson, L.A., Ndoye, A., Besacier, L. (2021). Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning. https://arxiv.org/abs/2103.08993

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Informasi Jurnal

Tahun Terbit: 2021
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓