SnakeSynth：面向生成式音频合成的新型交互
SnakeSynth: New Interactions for Generative Audio Synthesis
AI总结：
本文提出基于 Web 和 TensorFlow.js 的轻量合成器 SnakeSynth，利用二维触摸/拖拽手势实时控制深度生成音频的长度、强度与音色插值。
摘要：
我提出了“SnakeSynth”，这是一款基于网络的轻量级音频合成器，它将深度生成模型生成的音频与实时连续二维（2D）输入相结合，通过二维交互手势创建并控制长度可变的生成式声音。交互手势支持触摸和移动设备，并类比弹拨、拉奏和拨奏乐器的控制方式。点击与拖放手势可直接控制音频播放长度，而且我展示了声音长度和强度会通过与可编程二维坐标网格的交互而受到调制。借助基于浏览器的音频在速度和普及性方面的优势，以及 Google TensorFlow.js 中的硬件加速，我们生成了具有实时交互性的时变高保真声音。SnakeSynth 能够自适应地再现模型训练期间遇到的声音并在这些声音之间进行插值，尤其值得注意的是无需漫长训练时间；我还简要讨论了深度生成模型作为音乐表达交互范式的可能未来。
英文摘要：
I present "SnakeSynth," a web-based lightweight audio synthesizer that combines audio generated by a deep generative model and real-time continuous two-dimensional (2D) input to create and control variable-length generative sounds through 2D interaction gestures. Interaction gestures are touch and mobile-compatible with analogies to strummed, bowed, and plucked musical instrument controls. Point-and-click and drag-and-drop gestures directly control audio playback length and I show that sound length and intensity are modulated by interactions with a programmable 2D coordinate grid. Leveraging the speed and ubiquity of browser-based audio and hardware acceleration in Google's TensorFlow.js we generate time-varying high-fidelity sounds with real-time interactivity. SnakeSynth adaptively reproduces and interpolates between sounds encountered during model training, notably without long training times, and I briefly discuss possible futures for deep generative models as an interactive paradigm for musical expression.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
