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arXiv · 2605.13404

Seconds-Aligned PCA-DAC Latent Diffusion for Symbolic-to-Audio Drum Rendering

Konstantinos Soiledis·Maximos Kaliakatsos Papakostas·Dimos Makris·Konstantinos Tsamis
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Abstract

Symbolic-control drum generation requires preserving explicit event timing and dynamics while synthesizing acoustically plausible waveforms. We present Sec2Drum-DAC, a conditional latent-diffusion model for symbolic-to-audio drum rendering. The model conditions on event features sampled in physical time at codec-frame locations and predicts standardized principal-component coordinates of frozen DAC summed-codebook embeddings rather than waveform samples. In the evaluated DAC configuration, 72 principal components capture the observed training-frame summed-latent subspace under the stated SVD threshold, yielding a compact continuous denoising target with a deterministic reconstruction path to the 1024-dimensional DAC latent space before waveform decoding. Across 1,733 held-out four-beat windows, PCA diffusion improves paired spectral and transient metrics over deterministic PCA regression and a symbolic rendering baseline, while direct regression remains stronger on phase-sensitive waveform L1. Auxiliary RVQ cross-entropy improves short-step diffusion on mel error, onset-flux cosine, and waveform L1, with the most favorable trade-offs occurring at 6-25 denoising steps depending on the metric.

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Konstantinos Soiledis, Maximos Kaliakatsos Papakostas, Dimos Makris, Konstantinos Tsamis. 2026-05-13. Seconds-Aligned PCA-DAC Latent Diffusion for Symbolic-to-Audio Drum Rendering. https://arxiv.org/abs/2605.13404

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