Wavetable Synthesis Using CVAE for Timbre Control Based on Semantic Label

Synthesizers are essential in modern music production. However, their complex timbre parameters, often filled with technical terms, require expertise. This research introduces a method of timbre control in wavetable synthesis that is intuitive and sensible and utilizes semantic labels. Using a conditional variational autoencoder (CVAE), users can select a wavetable and define the timbre with labels such as bright, warm, and rich. The CVAE model, featuring convolutional and upsampling layers, effectively captures the wavetable nuances, ensuring real-time performance owing to their processing in the time domain. Experiments demonstrate that this approach allows for real-time, effective control of the timbre of the wavetable using semantic inputs and aims for intuitive timbre control through data-based semantic control. Audio examples are available on the online demo page<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>.

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Publication Details

Published
2024-12-03
DOI
https://doi.org/10.1109/apsipaasc63619.2025.10848699
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
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article

Wavetable Synthesis Using CVAE for Timbre Control Based on Semantic Label

Hiroko Terasawa, Shuyo Nakatani, Yuya Yamamoto, Tsugumasa Yutani
Music Technology and Sound Studies
article

Wavetable Synthesis Using CVAE for Timbre Control Based on Semantic Label

Hiroko Terasawa, Shuyo Nakatani, Yuya Yamamoto, Tsugumasa Yutani
article en

Abstract

Synthesizers are essential in modern music production. However, their complex timbre parameters, often filled with technical terms, require expertise. This research introduces a method of timbre control in wavetable synthesis that is intuitive and sensible and utilizes semantic labels. Using a conditional variational autoencoder (CVAE), users can select a wavetable and define the timbre with labels such as bright, warm, and rich. The CVAE model, featuring convolutional and upsampling layers, effectively captures the wavetable nuances, ensuring real-time performance owing to their processing in the time domain. Experiments demonstrate that this approach allows for real-time, effective control of the timbre of the wavetable using semantic inputs and aims for intuitive timbre control through data-based semantic control. Audio examples are available on the online demo page<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>.

University of Tsukuba (JP), CYBO (Japan) (JP)
Openalex Percentile: Top 74%
Music Technology and Sound Studies
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Wavetable Synthesis Using CVAE for Timbre Control Based on Semantic Label — Hiroko Terasawa, Shuyo Nakatani, et al. · (2024) | TGRS Research Map | TGRS