Toward a realistic model of speech processing in the brain with self-supervised learning. (arXiv:2206.01685v1 [q-bio.NC])

Several deep neural networks have recently been shown to generate activations
similar to those of the brain in response to the same input. These algorithms,
however, remain largely implausible: they require (1) extraordinarily large
amounts of data, (2) unobtainable supervised labels, (3) textual rather than
raw sensory input, and / or (4) implausibly large memory (e.g. thousands of
contextual words). These elements highlight the need to identify algorithms
that, under these limitations, would suffice to account for both behavioral and …

arxiv bio brain learning processing self-supervised learning speech speech processing supervised learning