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

Procedural audio may be defined as real-time sound generation according to programmatic
rules and live input. It is often considered a subset of sound synthesis and is especially …

The growing popularity of generative music models underlines the need for perceptually
relevant, objective music quality metrics. The Frechet Audio Distance (FAD) is commonly …

Multimodal datasets are ubiquitous in modern applications, and multimodal Variational
Autoencoders are a popular family of models that aim to learn a joint representation of …

This article presents a configurable version of Extreme Bandwidth Extension Network
(EBEN), a Generative Adversarial Network (GAN) designed to improve audio captured with …

Implicit Neural Representations (INRs) have emerged as a promising method for
representing diverse data modalities, including 3D shapes, images, and audio. While recent …

In recent years, text-to-music models have been the biggest breakthrough in automatic
music generation. While they are unquestionably a showcase of technological progress, it is …

Sound synthesizers are ubiquitous in modern music production but manipulating their
presets, ie the sets of synthesis parameters, demands expert skills. This study presents a …

In this study, we investigate the feasibility of utilizing state-of-the-art image perceptual
metrics for evaluating audio signals by representing them as spectrograms. The …

Over recent years generative models utilizing deep neural networks have demonstrated
outstanding capacity in synthesizing high-quality and plausible human speech and music …