June 7, 2024, 4:43 a.m. | Dulhan Jayalath, Gilad Landau, Brendan Shillingford, Mark Woolrich, Oiwi Parker Jones

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.04328v1 Announce Type: new
Abstract: The past few years have produced a series of spectacular advances in the decoding of speech from brain activity. The engine of these advances has been the acquisition of labelled data, with increasingly large datasets acquired from single subjects. However, participants exhibit anatomical and other individual differences, and datasets use varied scanners and task designs. As a result, prior work has struggled to leverage data from multiple subjects, multiple datasets, multiple tasks, and unlabelled datasets. …

abstract acquired acquisition advances arxiv brain brain activity cs.lg data datasets decoding however large datasets scaling self-supervised learning series speech supervised learning the engine type

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