Art2Song：通过情境音乐生成增强视觉艺术欣赏
Art2Song: Enhancing Visual Art Appreciation with Contextual Music Generation
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中文总结 AI 辅助
Art2Song 提出将视觉证据转为歌词、情境情绪融入配乐的音乐生成框架，以探索通过音乐增强视觉艺术欣赏的新模式。
中文摘要 AI 辅助
Art2Song 是一个概念性框架，通过将难以仅从图像感知的非视觉情境与视觉证据分离，将艺术作品表达为声音。视觉证据，如物体、颜色和空间构图，被转化为歌词，而源自博物馆艺术作品描述中历史与艺术史情境的情境情绪则反映在背景配乐中。Art2Song 并非以文本方式描述艺术作品，而是旨在探索一种新的艺术欣赏模式的可能性，在这种模式中，观众通过音乐体验隐藏的故事和情感情境。作为未来的交互方向，我们计划设计一个情感层混合滑块界面和一个结构化、可追踪的歌曲生成场景，从而展示用户能够探索视觉证据与情境情绪之间关系的可能性。
英文摘要
Art2Song is a conceptual framework that expresses artworks as sound by separating Non-Visual Context, which is difficult to perceive from the image alone, from Visual Evidence. Visual Evidence, such as objects, colors, and spatial composition, is transformed into Lyrics, while the Contextual Mood derived from the historical and art-historical context in the museum's artwork description is reflected in the background soundtrack. Rather than describing artworks textually, Art2Song aims to explore the possibility of a new mode of art appreciation in which viewers experience hidden stories and emotional context through music. As future interaction directions, we plan an Emotional Layer Blending Slider interface and a structured, traceable song-generation scenario, presenting the possibility that users can explore the relationship between Visual Evidence and Contextual Mood.
发表机构
- Pukyong National University（釜庆国立大学）
- Electronics and Telecommunications Research Institute（电子电信研究所）
机构由 AI 辅助整理，请以论文原文为准。
