Pitch-Conditioned Instrument Sound Synthesis From an Interactive Timbre Latent Space

• URL: http://arxiv.org/abs/2510.04339v1
• Date: Sun, 05 Oct 2025 20:03:30 GMT
• Title: Pitch-Conditioned Instrument Sound Synthesis From an Interactive Timbre Latent Space
• Authors: Christian Limberg, Fares Schulz, Zhe Zhang, Stefan Weinzierl,
• Abstract summary: This paper presents a novel approach to neural instrument sound synthesis using a two-stage semi-supervised learning framework.<n>We train a pitch-timbre disentangled 2D representation of audio samples using a Variational Autoencoder.<n>We use this representation as conditioning input for a Transformer-based generative model.
• Score: 6.12877670327196
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This paper presents a novel approach to neural instrument sound synthesis using a two-stage semi-supervised learning framework capable of generating pitch-accurate, high-quality music samples from an expressive timbre latent space. Existing approaches that achieve sufficient quality for music production often rely on high-dimensional latent representations that are difficult to navigate and provide unintuitive user experiences. We address this limitation through a two-stage training paradigm: first, we train a pitch-timbre disentangled 2D representation of audio samples using a Variational Autoencoder; second, we use this representation as conditioning input for a Transformer-based generative model. The learned 2D latent space serves as an intuitive interface for navigating and exploring the sound landscape. We demonstrate that the proposed method effectively learns a disentangled timbre space, enabling expressive and controllable audio generation with reliable pitch conditioning. Experimental results show the model's ability to capture subtle variations in timbre while maintaining a high degree of pitch accuracy. The usability of our method is demonstrated in an interactive web application, highlighting its potential as a step towards future music production environments that are both intuitive and creatively empowering: https://pgesam.faresschulz.com

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