用深度学习音乐变体工具，让创作者掌控创作过程与成果
Supporting Creative Ownership through Deep Learning-Based Music Variation
- 依赖音乐人输入质量的变体工具增强创作主导权
- 四週生態評估顯示，高手輸入可推動完整音樂構思
- 適合重視創作主體性的音樂家與人機協作研究者
本文探討音樂人工智慧設計中個人創作主權的重要性，研究實踐音樂人如何在作曲過程中保持創意控制。透過為期四週的生態評估，我們考察了一款依賴音樂人技能的音樂變體工具在實際創作環境中的運作情況。結果顯示，該工具對音樂人能力的高度依賴——包括提供優質初始音樂輸入，以及將靈感瞬間轉化為完整音樂概念——促進了對創作過程與作品本身的主權感。定性訪談進一步揭示了個人主權的重要性，並凸顯技術能力與藝術身份之間的張力。研究結果表明，音樂人工智慧應輔助而非取代人類創造力，強調設計工具時需保留音樂表達的人性特質。
原文摘要 · Abstract (English)
This paper investigates the importance of personal ownership in musical AI design, examining how practising musicians can maintain creative control over the compositional process. Through a four-week ecological evaluation, we examined how a music variation tool, reliant on the skill of musicians, functioned within a composition setting. Our findings demonstrate that the dependence of the tool on the musician's ability, to provide a strong initial musical input and to turn moments into complete musical ideas, promoted ownership of both the process and artefact. Qualitative interviews further revealed the importance of this personal ownership, highlighting tensions between technological capability and artistic identity. These findings provide insight into how musical AI can support rather than replace human creativity, highlighting the importance of designing tools that preserve the humanness of musical expression.
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