Overt speech decoding from cortical activity: a comparison of different linear methods.

ABSTRACT:

Introduction

Speech BCIs aim at reconstructing speech in real time from ongoing cortical activity. Ideal BCIs would need to reconstruct speech audio signal frame by frame on a millisecond-timescale. Such approaches require fast computation. In this respect, linear decoder are good candidates and have been widely used in motor BCIs. Yet, they have been very seldomly studied for speech reconstruction, and never for reconstruction of articulatory movements from intracranial activity. Here, we compared vanilla linear regression, ridge-regularized linear regressions, and partial least squares regressions for offline decoding of overt speech from cortical activity.

Methods

Two decoding paradigms were investigated: (1) direct decoding of acoustic vocoder features of speech, and (2)

SUBMITTER: Le Godais G 

PROVIDER: S-EPMC10326283 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature