DeformTune: A Deformable XAI Music Prototype for Non-Musicians
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908475010842624 |
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| author | Xu, Ziqing Bryan-Kinns, Nick |
| author_facet | Xu, Ziqing Bryan-Kinns, Nick |
| contents | Many existing AI music generation tools rely on text prompts, complex interfaces, or instrument-like controls, which may require musical or technical knowledge that non-musicians do not possess. This paper introduces DeformTune, a prototype system that combines a tactile deformable interface with the MeasureVAE model to explore more intuitive, embodied, and explainable AI interaction. We conducted a preliminary study with 11 adult participants without formal musical training to investigate their experience with AI-assisted music creation. Thematic analysis of their feedback revealed recurring challenge--including unclear control mappings, limited expressive range, and the need for guidance throughout use. We discuss several design opportunities for enhancing explainability of AI, including multimodal feedback and progressive interaction support. These findings contribute early insights toward making AI music systems more explainable and empowering for novice users. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_00160 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | DeformTune: A Deformable XAI Music Prototype for Non-Musicians Xu, Ziqing Bryan-Kinns, Nick Human-Computer Interaction Artificial Intelligence Sound Audio and Speech Processing Many existing AI music generation tools rely on text prompts, complex interfaces, or instrument-like controls, which may require musical or technical knowledge that non-musicians do not possess. This paper introduces DeformTune, a prototype system that combines a tactile deformable interface with the MeasureVAE model to explore more intuitive, embodied, and explainable AI interaction. We conducted a preliminary study with 11 adult participants without formal musical training to investigate their experience with AI-assisted music creation. Thematic analysis of their feedback revealed recurring challenge--including unclear control mappings, limited expressive range, and the need for guidance throughout use. We discuss several design opportunities for enhancing explainability of AI, including multimodal feedback and progressive interaction support. These findings contribute early insights toward making AI music systems more explainable and empowering for novice users. |
| title | DeformTune: A Deformable XAI Music Prototype for Non-Musicians |
| topic | Human-Computer Interaction Artificial Intelligence Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2508.00160 |