用雷达感应生理信号，生成有情感和文化特色的音乐。
BREATH: A Bio-Radar Embodied Agent for Tonal and Human-Aware Diffusion Music Generation
- 通过毫米波雷达捕捉心率呼吸，结合环境信息推理出音乐特征。
- 生理变化可有效调节音乐节奏与情绪强度，且五声音阶嵌入提升文化契合度。
- 适合关注身心互动、疗愈音乐与人机协同创作的研究者与艺术家。
我们提出一种多模态个性化音乐生成系统，融合生理传感、基于大语言模型的推理与可控音频合成。毫米波雷达非侵入式采集心率与呼吸频率，这些生理信号结合环境状态，由推理代理解析为符号化音乐描述符，如节奏、情绪强度及中国传统五声音阶模式，并以结构化提示引导基于扩散模型的音频生成器合成富有表现力的旋律。系统强调音调嵌入的文化根基，实现自适应的具身音乐交互。通过研究创作方法论，结合案例研究、专家反馈与受控实验评估。结果表明，生理波动能有意义地调节音乐特征，音调条件化显著增强与目标调式特征的一致性。专家用户认为系统提供直观、富有文化共鸣的音乐响应，凸显其在治疗与交互应用中的潜力。本工作展示了一种连接雷达感知、提示推理与生成音频建模的新型生物音乐反馈闭环。
原文摘要 · Abstract (English)
We present a multimodal system for personalized music generation that integrates physiological sensing, LLM-based reasoning, and controllable audio synthesis. A millimeter-wave radar sensor non-invasively captures heart rate and respiration rate. These physiological signals, combined with environmental state, are interpreted by a reasoning agent to infer symbolic musical descriptors, such as tempo, mood intensity, and traditional Chinese pentatonic modes, which are then expressed as structured prompts to guide a diffusion-based audio model in synthesizing expressive melodies. The system emphasizes cultural grounding through tonal embeddings and enables adaptive, embodied music interaction. To evaluate the system, we adopt a research-creation methodology combining case studies, expert feedback, and targeted control experiments. Results show that physiological variations can modulate musical features in meaningful ways, and tonal conditioning enhances alignment with intended modal characteristics. Expert users reported that the system affords intuitive, culturally resonant musical responses and highlighted its potential for therapeutic and interactive applications. This work demonstrates a novel bio-musical feedback loop linking radar-based sensing, prompt reasoning, and generative audio modeling.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。