| Sumario: | 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.
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