Conveners
A14.08 Computational and AI approaches in audiology: S105
- Volker Hohmann (Carl von Ossietzky Universität Oldenburg)
- Mark Saddler (Technical University of Denmark)
A14.08 Computational and AI approaches in audiology: S332
- Mark Saddler (Technical University of Denmark)
- Volker Hohmann (Carl von Ossietzky Universität Oldenburg)
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Hartmut Schoon (Carl von Ossietzky Universität Oldenburg)10/09/2026, 08:40A14 Physiological Acoustics and Audiology
Models that predict auditory perception are important tools to quantify the effect of sound processing, for instance, speech enhancement algorithms in communication systems or in hearing aids. Non-intrusive models which do not rely on a clean reference signal could potentially be applied in real-world settings if they generalize well in broadly varying acoustic conditions. This contribution...
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Annesya Banerjee (Harvard University)10/09/2026, 09:00A14 Physiological Acoustics and Audiology
Cochlear implants (CIs) aim to enable hearing in people with severe hearing loss by electrically stimulating the auditory nerve. Although highly successful, CIs fail to restore normal perception in many listening situations. We propose a deep learning framework to evaluate factors limiting CI-mediated perception in real-world auditory tasks. We optimized deep artificial neural network decoders...
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Christian Koch (Physikalisch-Technische Bundesanstalt)10/09/2026, 09:20A14 Physiological Acoustics and Audiology
The utilization of artificial intelligence in critical and high-risk applications is poised to become a prevalent practice soon and the development of a methodology for testing and approving machine or deep learning models is imperative. As most experience has been accumulated in the medical field to date, this contribution employs a classification task using electroencephalography data to...
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Mareike Buhl (Medical Physics, University of Oldenburg)10/09/2026, 09:40A14 Physiological Acoustics and Audiology
Clinical decision-support systems (CDSS) can support experts’ decision-making by exploiting big data. For example, a classification integrated into the CDSS can provide a statistical proposition of which hearing device a patient would benefit from; or data-driven, unsupervised approaches can characterize patient groups available in the data, showing different profiles of audiological test...
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Gerard Encina-Llamas (University of Vic - Central University of Catalonia)10/09/2026, 10:20A14 Physiological Acoustics and Audiology
The aetiology of hearing impairment is multifactorial, involving numerous structures within the auditory system. Although pure-tone audiometry remains the clinical gold standard for hearing device fitting, it lacks sensitivity to certain pathologies, including hidden hearing damage. Previous approaches to phenotype classification either relied solely on audiogram data or incorporated...
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Gloria Araiza-Illan (University Medical Center Groningen)10/09/2026, 10:40A14 Physiological Acoustics and Audiology
Two of the main challenges that the hearing care workforce currently face concern the limited resources and the increasing number of older adults who are in need of hearing screening. New technology tools, such as automatic speech recognition (ASR), have the potential to revolutionise the field. However, state-of-the-art ASR systems are predominantly trained on speech from healthy young adult...
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Jan-Willem Wasmann (Radboudumc)10/09/2026, 11:00A14 Physiological Acoustics and Audiology
Objectives: This study investigated the feasibility, acceptability, and perceived benefits of conducting cochlear implant (CI) remote fitting in real-life listening situations.Methods: Twelve post-lingually deafened CI users participated in four sessions: a baseline in-clinic visit, two remote fitting sessions (at home and in a real-life setting), and a final in-clinic evaluation. Participants...
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Jan-Willem Wasmann (Radboudumc)10/09/2026, 11:20A14 Physiological Acoustics and Audiology
ObjectivesThis study introduces a novel approach aimed at improving phoneme confusion errors among adult CI users through individualized phoneme training via a mobile app.MethodsTwenty-five experienced adult CI users with a post-lingual onset of severe-to-profound hearing loss were invited to participate in a four-week phoneme training program using a mobile app. Participants were instructed...
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