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Differentiable digital signal processing (DDSP) techniques, including methodsfor audio synthesis, have gained attention in recent years and lend themselvesto interpretability in the parameter space. However, current differentiablesynthesis methods have not explicitly sought to model the transient portion ofsignals, which is important for percussive sounds. In this work, we present aunified synthesis framework aiming to address transient generation andpercussive synthesis within a DDSP framework. To this end, we propose a modelfor percussive synthesis that builds on sinusoidal modeling synthesis andincorporates a modulated temporal convolutional network for transientgeneration. We use a modified sinusoidal peak picking algorithm to generatetime-varying non-harmonic sinusoids and pair it with differentiable noise andtransient encoders that are jointly trained to reconstruct drumset sounds. Wecompute a set of reconstruction metrics using a large dataset of acoustic andelectronic percussion samples that show that our method leads to improved onsetsignal reconstruction for membranophone percussion instruments.

Differentiable Modelling of Percussive Audio with Transient and Spectral Synthesis