Mozualization: Crafting Music and Visual Representation with Multimodal AI
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866910914289074176 |
|---|---|
| author | Xu, Wanfang Zhao, Lixiang Song, Haiwen Song, Xinheng Lu, Zhaolin Liu, Yu Chen, Min Lim, Eng Gee Yu, Lingyun |
| author_facet | Xu, Wanfang Zhao, Lixiang Song, Haiwen Song, Xinheng Lu, Zhaolin Liu, Yu Chen, Min Lim, Eng Gee Yu, Lingyun |
| contents | In this work, we introduce Mozualization, a music generation and editing tool that creates multi-style embedded music by integrating diverse inputs, such as keywords, images, and sound clips (e.g., segments from various pieces of music or even a playful cat's meow). Our work is inspired by the ways people express their emotions -- writing mood-descriptive poems or articles, creating drawings with warm or cool tones, or listening to sad or uplifting music. Building on this concept, we developed a tool that transforms these emotional expressions into a cohesive and expressive song, allowing users to seamlessly incorporate their unique preferences and inspirations. To evaluate the tool and, more importantly, gather insights for its improvement, we conducted a user study involving nine music enthusiasts. The study assessed user experience, engagement, and the impact of interacting with and listening to the generated music. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_13891 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Mozualization: Crafting Music and Visual Representation with Multimodal AI Xu, Wanfang Zhao, Lixiang Song, Haiwen Song, Xinheng Lu, Zhaolin Liu, Yu Chen, Min Lim, Eng Gee Yu, Lingyun Human-Computer Interaction Artificial Intelligence In this work, we introduce Mozualization, a music generation and editing tool that creates multi-style embedded music by integrating diverse inputs, such as keywords, images, and sound clips (e.g., segments from various pieces of music or even a playful cat's meow). Our work is inspired by the ways people express their emotions -- writing mood-descriptive poems or articles, creating drawings with warm or cool tones, or listening to sad or uplifting music. Building on this concept, we developed a tool that transforms these emotional expressions into a cohesive and expressive song, allowing users to seamlessly incorporate their unique preferences and inspirations. To evaluate the tool and, more importantly, gather insights for its improvement, we conducted a user study involving nine music enthusiasts. The study assessed user experience, engagement, and the impact of interacting with and listening to the generated music. |
| title | Mozualization: Crafting Music and Visual Representation with Multimodal AI |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2504.13891 |