Brain-informed speech separation (BISS) for enhancement of target speaker in multitalker speech perception

Copyright © 2020. Published by Elsevier Inc..

Hearing-impaired people often struggle to follow the speech stream of an individual talker in noisy environments. Recent studies show that the brain tracks attended speech and that the attended talker can be decoded from neural data on a single-trial level. This raises the possibility of "neuro-steered" hearing devices in which the brain-decoded intention of a hearing-impaired listener is used to enhance the voice of the attended speaker from a speech separation front-end. So far, methods that use this paradigm have focused on optimizing the brain decoding and the acoustic speech separation independently. In this work, we propose a novel framework called brain-informed speech separation (BISS)1 in which the information about the attended speech, as decoded from the subject's brain, is directly used to perform speech separation in the front-end. We present a deep learning model that uses neural data to extract the clean audio signal that a listener is attending to from a multi-talker speech mixture. We show that the framework can be applied successfully to the decoded output from either invasive intracranial electroencephalography (iEEG) or non-invasive electroencephalography (EEG) recordings from hearing-impaired subjects. It also results in improved speech separation, even in scenes with background noise. The generalization capability of the system renders it a perfect candidate for neuro-steered hearing-assistive devices.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:223

Enthalten in:

NeuroImage - 223(2020) vom: 15. Dez., Seite 117282

Sprache:

Englisch

Beteiligte Personen:

Ceolini, Enea [VerfasserIn]
Hjortkjær, Jens [VerfasserIn]
Wong, Daniel D E [VerfasserIn]
O'Sullivan, James [VerfasserIn]
Raghavan, Vinay S [VerfasserIn]
Herrero, Jose [VerfasserIn]
Mehta, Ashesh D [VerfasserIn]
Liu, Shih-Chii [VerfasserIn]
Mesgarani, Nima [VerfasserIn]

Links:

Volltext

Themen:

Cognitive control
Deep learning
EEG
Hearing aid
Journal Article
Neuro-steered
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Speech separation

Anmerkungen:

Date Completed 03.03.2021

Date Revised 31.07.2021

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1016/j.neuroimage.2020.117282

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM314025553