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arXiv · 2508.08684

Out of the Box, into the Clinic? Evaluating State-of-the-Art ASR for Clinical Applications for Older Adults

Bram van Dijk·Tiberon Kuiper·Sirin Aoulad si Ahmed·Armel Levebvre·Jake Johnson·Jan Duin·Simon Mooijaart·Marco Spruit
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Abstract

Voice-controlled interfaces can support older adults in clinical contexts -- with chatbots being a prime example -- but reliable Automatic Speech Recognition (ASR) for underrepresented groups remains a bottleneck. This study evaluates state-of-the-art ASR models on language use of older Dutch adults, who interacted with the Welzijn.AI chatbot designed for geriatric contexts. We benchmark generic multilingual ASR models, and models fine-tuned for Dutch spoken by older adults, while also considering processing speed. Our results show that generic multilingual models outperform fine-tuned models, which suggests recent ASR models can generalise well out of the box to real-world datasets. Moreover, our results indicate that truncating generic models is helpful in balancing the accuracy-speed trade-off. Nonetheless, we also find inputs which cause a high word error rate and place them in context.

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Bram van Dijk, Tiberon Kuiper, Sirin Aoulad si Ahmed, Armel Levebvre, Jake Johnson, Jan Duin, Simon Mooijaart, Marco Spruit. 2025-10-01. Out of the Box, into the Clinic? Evaluating State-of-the-Art ASR for Clinical Applications for Older Adults. https://arxiv.org/abs/2508.08684

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