  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.
