从演示中拯救性能：与打击乐手共同设计鼓手势映射
Rescuing Performance from the Demo: Co-Designing Drum Gesture Mappings with a Percussionist
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中文总结 AI 辅助
本研究与专业打击乐手共同设计鼓手势映射工具包，利用生产性不和谐概念平衡美学与技术约束，开发连续手势识别方法，并探讨技术影响与隐性知识的作用。
中文摘要 AI 辅助
用传感器和神经网络映射来增强乐器是一种已被充分探索的数字乐器设计方法。虽然增强可以创造新的表现机会，但它们也会施加美学影响，并可能限制音乐家的手势语言，如果不加以控制，这可能导致技术捕获。为了研究这一点，我们与一位专业打击乐手进行了一项研究，共同开发了一个手势映射工具包，并录制了一张包含十首曲目的专辑。借鉴生产性不和谐的概念，我们的研究旨在将音乐家的美学与技术约束保持张力。这连同基于实践的反思方法，支持了用于打击乐映射的连续手势识别方法的开发，并揭示了对设计过程的见解。我们识别出“知道何时”作为一种隐性知识形式，它支持了生产性不和谐，并提出了一个开放性问题：在缺乏音乐家更广泛的社会背景的情况下，我们如何知道技术的影响是否真正支持他们的实践？
英文摘要
Augmenting instruments with sensors and neural network mappings is a well-explored digital musical instrument design approach. While augmentations can create new expressive opportunities, they also exert aesthetic influence and can constrain musicians' gestural language, which, if left unchecked, can lead to technological capture. To examine this, we conducted a study with a professional percussionist, co-developing a gesture mapping toolkit and recording a ten-track album. Drawing on the concept of productive dissonance, our study aimed to hold the musician's aesthetic in tension with technological constraints. This, along with a practice-based reflective approach, supported the development of a continuous gesture recognition method for percussive mapping and surfaced insights into the design process. We identify knowing-when as a form of tacit knowledge that supported productive dissonance, and raise an open question: absent a musician's broader social context, how do we know whether a technology's influence is genuinely supporting their practice?
发表机构
- Queen Mary University of London（伦敦玛丽女王大学）
- Ableton AG（Ableton公司）
- Imperial College London（帝国理工学院）
机构由 AI 辅助整理，请以论文原文为准。
