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

• URL: http://arxiv.org/abs/2103.08993v1
• Date: Tue, 16 Mar 2021 11:37:03 GMT
• Title: Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning
• Authors: Jama Hussein Mohamud, Lloyd Acquaye Thompson, Aissatou Ndoye, and Laurent Besacier
• Abstract summary: 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, 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.
• Score: 13.7466513616362
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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