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Abstract
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.
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.
| Original language | English |
|---|---|
| Pages (from-to) | EL227-EL233 |
| Number of pages | 7 |
| Journal | The Journal of the Acoustical Society of America |
| Volume | 148 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 8 Sept 2020 |
Keywords
- hearing aids
- automatic speech recognition
- fitting rule
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Dive into the research topics of 'Improving hearing-aid gains based on automatic speech recognition'. Together they form a unique fingerprint.Projects
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Manchester Centre for Audiology and Deafness (ManCAD)
Munro, K. (PI), Millman, R. (PI), Lamb, W. (Support team), Dawes, P. (PI), Plack, C. (PI), Stone, M. (PI), Kluk-De Kort, K. (PI), Moore, D. (PI), Morton, C. (PI), Prendergast, G. (PI), Couth, S. (PI), Schlittenlacher, J. (PI), Chilton, H. (PI), Visram, A. (Researcher), Dillon, H. (PI), Guest, H. (Researcher), Heinrich, A. (PI), Jackson, I. (Researcher), Littlejohn, J. (Researcher), Jones, L. (PI), Lough, M. (Researcher), Morgan, R. (Researcher), Perugia, E. (Researcher), Roughley, A. (Researcher), Whiston, H. (Researcher), Wright, C. (Support team), Saunders, G. (PI), Kelly, C. (PI), Cross, H. (Researcher), Loughran, M. (Researcher), Hoseinabadi, R. (PI) & Vercammen, C. (PI)
Project: Research
Research output
- 1 Article
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OPRA-RS: A Hearing-Aid Fitting Method Based on Automatic Speech Recognition and Random Search
Goncalves Braz, L., Fontan, L., Pinquier, J., Stone, M. & Fullgrabe, C., 21 Feb 2022, In: Frontiers in Neuroscience.Research output: Contribution to journal › Article › peer-review
Open Access