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

• URL: http://arxiv.org/abs/2508.08684v3
• Date: Wed, 01 Oct 2025 07:06:51 GMT
• Title: Out of the Box, into the Clinic? Evaluating State-of-the-Art ASR for Clinical Applications for Older Adults
• Authors: Bram van Dijk, Tiberon Kuiper, Sirin Aoulad si Ahmed, Armel Levebvre, Jake Johnson, Jan Duin, Simon Mooijaart, Marco Spruit,
• Abstract summary: This study evaluates state-of-the-art Automatic Speech Recognition (ASR) models on language use of older Dutch adults.<n>We benchmark generic multilingual ASR models, and models fine-tuned for Dutch spoken by older adults.<n>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.
• Score: 2.01562032767537
• License: http://creativecommons.org/licenses/by/4.0/
• 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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