Research and Development of an AI Music Therapist – Toward Digital Therapeutics of Music Therapy

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Abstract

This paper describes research into the development of an artificial intelligence (AI) based music therapist (AI music therapist) for elderly people with dementia. Music therapy is expected to be effective for the ‘behavioural and psychological symptoms’ of dementia and thus contribute to reducing the burden of caregiving. However, the number of music therapists in Japan is very small compared to the number of elderly people with dementia, and not all elderly people with dementia in Japan have easy access to music therapy. Therefore, in order to enable elderly people with dementia to receive music therapy anytime, anywhere and as many times as possible, we are developing a virtual music therapist (AI music therapist) called ‘Satsuki-san’, who appears on a computer screen. In this paper, we report on the latest version of ‘Satsuki-san’ and collect opinions from caregivers actually engaged in the care of elderly people with dementia and music therapists with extensive clinical practice experience with elderly people with dementia. The opinions of the caregivers and music therapists showed a high level of expectation for the AI music therapist, but they also pointed out a number of problems, for example about Satsuki’s speech, such as the need for more intonation. The music therapists also pointed out a number of areas for improvement with regard to singing accompaniment. In the future, we would like to collect a variety of data from the subjects of music therapy through the use of the AI music therapists and establish a music digital therapeutics that can objectively evaluate the subjects’ condition and predict the progression of dementia.

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APA

Kosugi, N., Ishii, K., & Kodama, N. (2025). Research and Development of an AI Music Therapist – Toward Digital Therapeutics of Music Therapy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 15343 LNCS, pp. 151–166). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-78093-6_13

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