PLAUD的架构与可供性：表演式隐变量与无监督DDSP
Architecture and Affordances of PLAUD: Performative Latents and Unsupervised DDSP
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中文总结 AI 辅助
本文介绍了基于NoiseBandNet构建的神经合成器PLAUD的架构、交互方式，结合可供性分析指出其表演特性源于架构，为现场电子音乐表演提供了技术说明与情境化分析。
中文摘要 AI 辅助
PLAUD（Performative Latents and Unsupervised DDSP，表演式隐变量与无监督DDSP）是一款基于NoiseBandNet构建、在小型个人声音语料库上训练的神经合成器及Max for Live现场电子音乐工具。本文介绍其架构，结合变分DDSP合成模型、隐变量平滑、多尺度频谱与对抗损失，以及可选的Transformer先验，还包含直接作用于合成链的一系列弯曲操作：组件限制、波形整形与先验反馈。Max for Live界面将控制生成、轨迹采样与调制作为主要交互模式。全文贯穿可供性分析，指出该系统的表演特性源于架构决策而非在其之上设计，本文既贡献了该系统的技术说明，也对其在现场电子音乐表演中的角色进行了情境化可供性分析。
英文摘要
PLAUD (Performative Latents and Unsupervised DDSP) is a neural synthesizer and Max for Live instrument for live electronic music, built on NoiseBandNet and trained on small personal sound corpora. We present its architecture, combining a variational DDSP synthesis model, latent smoothing, multi-scale spectral and adversarial losses, and an optional transformer prior, alongside a set of bending operations that intervene directly in the synthesis chain: component limiting, waveshaping, and prior feedback. The Max for Live interface exposes control generation, trajectory sampling, and modulation as primary modes of interaction. Throughout, we thread an affordance analysis arguing that the system's performative character follows from architectural decisions rather than being designed on top of them. The paper contributes both a technical account of the system and a situated affordance analysis of its role in live electronic music performance.
发表机构
- Music Technology Group Universitat Pompeu Fabra（庞培法布拉大学音乐技术组）
机构由 AI 辅助整理，请以论文原文为准。
