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

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