Fontan_etal_JASAEL20.pdf (1.4 MB)
Download fileImproving hearing-aid gains based on automatic speech recognition
journal contribution
posted on 2020-10-13, 09:25 authored by Lionel Fontan, Maxime Le Coz, Charlotte Azzopardi, Michael A Stone, Christian FullgrabeThis 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 AmericaVolume
148Issue
3Pages
EL227 - EL233Publisher
Acoustical Society of America (ASA)Version
- VoR (Version of Record)
Rights holder
© The authorsPublisher 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
2020-08-13Publication date
2020-09-08Copyright date
2020ISSN
0001-4966eISSN
1520-8524Publisher version
Language
- en