English

Speech Synthesis using EEG

Audio and Speech Processing 2020-05-05 v2 Machine Learning Sound Quantitative Methods Machine Learning

Abstract

In this paper we demonstrate speech synthesis using different electroencephalography (EEG) feature sets recently introduced in [1]. We make use of a recurrent neural network (RNN) regression model to predict acoustic features directly from EEG features. We demonstrate our results using EEG features recorded in parallel with spoken speech as well as using EEG recorded in parallel with listening utterances. We provide EEG based speech synthesis results for four subjects in this paper and our results demonstrate the feasibility of synthesizing speech directly from EEG features.

Keywords

Cite

@article{arxiv.2002.12756,
  title  = {Speech Synthesis using EEG},
  author = {Gautam Krishna and Co Tran and Yan Han and Mason Carnahan},
  journal= {arXiv preprint arXiv:2002.12756},
  year   = {2020}
}

Comments

Accepted for publication at IEEE ICASSP 2020

R2 v1 2026-06-23T13:57:43.584Z