Understanding Human-AI Collaboration in Music Therapy Through Co-Design with Therapists
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866914752706379776 |
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| author | Sun, Jingjing Yang, Jingyi Zhou, Guyue Jin, Yucheng Gong, Jiangtao |
| author_facet | Sun, Jingjing Yang, Jingyi Zhou, Guyue Jin, Yucheng Gong, Jiangtao |
| contents | The rapid development of musical AI technologies has expanded the creative potential of various musical activities, ranging from music style transformation to music generation. However, little research has investigated how musical AIs can support music therapists, who urgently need new technology support. This study used a mixed method, including semi-structured interviews and a participatory design approach. By collaborating with music therapists, we explored design opportunities for musical AIs in music therapy. We presented the co-design outcomes involving the integration of musical AIs into a music therapy process, which was developed from a theoretical framework rooted in emotion-focused therapy. After that, we concluded the benefits and concerns surrounding music AIs from the perspective of music therapists. Based on our findings, we discussed the opportunities and design implications for applying musical AIs to music therapy. Our work offers valuable insights for developing human-AI collaborative music systems in therapy involving complex procedures and specific requirements. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_14503 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Human-AI Collaboration in Music Therapy Through Co-Design with Therapists Sun, Jingjing Yang, Jingyi Zhou, Guyue Jin, Yucheng Gong, Jiangtao Human-Computer Interaction H.5.2 The rapid development of musical AI technologies has expanded the creative potential of various musical activities, ranging from music style transformation to music generation. However, little research has investigated how musical AIs can support music therapists, who urgently need new technology support. This study used a mixed method, including semi-structured interviews and a participatory design approach. By collaborating with music therapists, we explored design opportunities for musical AIs in music therapy. We presented the co-design outcomes involving the integration of musical AIs into a music therapy process, which was developed from a theoretical framework rooted in emotion-focused therapy. After that, we concluded the benefits and concerns surrounding music AIs from the perspective of music therapists. Based on our findings, we discussed the opportunities and design implications for applying musical AIs to music therapy. Our work offers valuable insights for developing human-AI collaborative music systems in therapy involving complex procedures and specific requirements. |
| title | Understanding Human-AI Collaboration in Music Therapy Through Co-Design with Therapists |
| topic | Human-Computer Interaction H.5.2 |
| url | https://arxiv.org/abs/2402.14503 |