Fatehifar, M., Schlittenlacher, J., Almufarrij, I. et al. (3 more authors) (2025) Applications of automatic speech recognition and text-to-speech technologies for hearing assessment: a scoping review. International Journal of Audiology, 64 (6). pp. 537-548. ISSN: 1499-2027
Abstract
OBJECTIVE: Exploring applications of automatic speech recognition and text-to-speech technologies in hearing assessment and evaluations of hearing aids. DESIGN: Review protocol was registered at the INPLASY database and was performed following the PRISMA scoping review guidelines. A search in ten databases was conducted in January 2023 and updated in June 2024. STUDY SAMPLE: Studies that used automatic speech recognition or text-to-speech to assess measures of hearing ability (e.g. speech reception threshold), or to configure hearing aids were retrieved. Of the 2942 records found, 28 met the inclusion criteria. RESULTS: The results indicated that text-to-speech could effectively replace recorded stimuli in speech intelligibility tests, requiring less effort for experimenters, without negatively impacting outcomes (n = 5). Automatic speech recognition captured verbal responses accurately, allowing for reliable speech reception threshold measurements without human supervision (n = 7). Moreover, automatic speech recognition was employed to simulate participants' hearing, with high correlations between simulated and empirical data (n = 14). Finally, automatic speech recognition was used to optimise hearing aid configurations, leading to higher speech intelligibility for wearers compared to the original configuration (n = 3). CONCLUSIONS: There is the potential for automatic speech recognition and text-to-speech systems to enhance accessibility of, and efficiency in, hearing assessments, offering unsupervised testing options, and facilitating hearing aid personalisation.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of British Society of Audiology, International Society of Audiology, and Nordic Audiological Society. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
| Keywords: | Automatic speech recognition; hearing assessment; hearing test; hearing aid; hearing in noise test; speech in noise; text to speech |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) |
| Date Deposited: | 05 Feb 2026 13:04 |
| Last Modified: | 05 Feb 2026 13:04 |
| Status: | Published |
| Publisher: | Taylor & Francis |
| Identification Number: | 10.1080/14992027.2024.2422390 |
| Related URLs: | |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:237550 |

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