Analyzing the factors affecting usefulness of Self-Supervised Pre-trained Representations for Speech Recognition. (arXiv:2203.16973v3 [cs.CL] UPDATED)

Self-supervised learning (SSL) to learn high-level speech representations has
been a popular approach to building Automatic Speech Recognition (ASR) systems
in low-resource settings. However, the common assumption made in literature is
that a considerable amount of unlabeled data is available for the same domain
or language that can be leveraged for SSL pre-training, which we acknowledge is
not feasible in a real-world setting. In this paper, as part of the Interspeech
Gram Vaani ASR challenge, we try to study the …

arxiv speech speech recognition