The term “differentiable digital signal processing” describes a family of techniques in which
loss function gradients are backpropagated through digital signal processors, facilitating …

We present a framework that can impose the audio effects and production style from one
recording to another by example with the goal of simplifying the audio production process …

Differentiable Wavetable Synthesis (DWTS) is a technique for neural audio synthesis which
learns a dictionary of one-period waveforms ie wavetables, through end-to-end training. We …

In this paper we integrate classic adaptive filtering algorithms with modern deep learning to
propose a new approach called deep adaptive AEC. The main idea is to represent the linear …

A vocoder is a conditional audio generation model that converts acoustic features such as
mel-spectrograms into waveforms. Taking inspiration from Differentiable Digital Signal …

While synthesizers have become commonplace in music production, many users find it
difficult to control the parameters of a synthesizer to create a sound as they intended. In …

We propose an end-to-end music mixing style transfer system that converts the mixing style
of an input multitrack to that of a reference song. This is achieved with an encoder pre …

While synthesizers have become commonplace in music production, many users find it
difficult to control the parameters of a synthesizer to create the intended sound. In order to …

This paper presents DiffMoog-a differentiable modular synthesizer with a comprehensive set
of modules typically found in commercial instruments. Being differentiable, it allows …

In this article, we investigate the notion of model-based deep learning in the realm of music
information research (MIR). Loosely speaking, we refer to the term model-based deep …