neural-speech-decoding

This paper proposes an end-to-end Conformer-based neural decoder for intracortical speech decoding from a participant with ALS, achieving a 23.80% character error rate without any external language model. It demonstrates that meaningful character-level decoding is possible in a fully end-to-end framework.