声音画布：将算法嵌入网络化、具感官的声音艺术中
Sounding Canvas: Embedding Algorithms in Networked, Sensorial Sound Art
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中文总结 AI 辅助
本研究将算法嵌入声音艺术装置，通过离线视觉-声音映射与在线模型实现触摸响应的多模态交互，引发算法艺术相关问题。
中文摘要 AI 辅助
声音画布将绘画转变为可触摸响应的多模态装置，其内部嵌入了电容传感器、实时决策模型与网络设备。触摸会触发空间化声音，仿佛从绘画本身发出。该作品在三个层面嵌入算法：感知层面，通过离线视觉-声音映射将绘画特征与声音描述符对齐；技术层面，采用基于CNN的离线映射定义声音词汇，结合两个在线事件管理器——高阶马尔可夫模型与基于LSTM的策略，在响应性与引导探索间取得平衡；表演层面，通过在线模型塑造与参观者及网络上远程画布的实时交互。我们阐述了艺术理念与技术实现，探讨这些层如何让算法通过行为而非代码被感知，网络如何将个体触摸转变为分布式共同创作，以及该系统如何引发嵌入式算法艺术中关于作者身份、能动性与评价的问题。
英文摘要
Sounding Canvas turns painting into a touch-responsive multimodal installation by embedding capacitive sensors, real-time decision models, and networking inside the canvas. Touches trigger spatialised sounds that appear to emanate from the painting itself. The work embeds algorithms physically, as sensing and computation concealed behind the artwork; perceptually, through an offline visual-to-sonic mapping that aligns a painting's features with sound descriptors; and performatively, through online models that shape live interaction with visitors and with remote canvases over a network. We describe the artistic rationale and technical implementation, combining a CNN-based offline mapping that defines the sound vocabulary with two online event managers, a higher-order Markov model and an LSTM-based policy, that balance responsiveness with guided exploration. We discuss how these layers make algorithms perceptible through behaviour rather than code, how networking transforms solitary touch into distributed co-authorship, and how the system raises questions of authorship, agency, and evaluation in embedded algorithmic artworks.
