Semantic alignment of EEG and text: a contrastive learning framework for decoding imagined speech
Read the original at arxiv.org→arXiv:2610.20766v1 Announce Type: new Abstract: Imagined speech decoding from EEG offers a promising route toward naturalistic brain-computer interfaces. Traditional closed-set classifiers treat semantic categories...
Original headline: "Semantic Alignment of EEG and Text: A Contrastive Learning Framework for Decoding Imagined Speech"
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- Oct 16, 04:00 UTC arXiv cs.LG lead source Semantic Alignment of EEG and Text: A Contrastive Learning Framework for Decoding Imagined Speech