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Improving hearing-aid gains based on automatic speech recognition

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journal contribution
posted on 2020-10-13, 09:25 authored by Lionel Fontan, Maxime Le Coz, Charlotte Azzopardi, Michael A Stone, Christian Fullgrabe
This study provides proof of concept that automatic speech recognition (ASR) can be used to improve hearing aid (HA) fitting. A signal-processing chain consisting of a HA simulator, a hearing-loss simulator, and an ASR system normalizing the intensity of input signals was used to find HA-gain functions yielding the highest ASR intelligibility scores for individual audiometric profiles of 24 listeners with age-related hearing loss. Significantly higher aided speech intelligibility scores and subjective ratings of speech pleasantness were observed when the participants were fitted with ASR-established gains than when fitted with the gains recommended by the CAM2 fitting rule.

History

School

  • Sport, Exercise and Health Sciences

Published in

The Journal of the Acoustical Society of America

Volume

148

Issue

3

Pages

EL227 - EL233

Publisher

Acoustical Society of America (ASA)

Version

  • VoR (Version of Record)

Rights holder

© The authors

Publisher statement

This is an Open Access Article. It is published by Acoustical Society of America (ASA) under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

2020-08-13

Publication date

2020-09-08

Copyright date

2020

ISSN

0001-4966

eISSN

1520-8524

Language

  • en

Depositor

Dr Christian Fullgrabe . Deposit date: 10 October 2020

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