This paper proposes a model that generates a drum track in the audio domain to play along
to a user-provided drum-free recording. Specifically, using paired data of drumless tracks …

Generative Adversarial Networks (GANs) have achieved excellent audio synthesis quality in
the last years. However, making them operable with semantically meaningful controls …

This paper proposes a new benchmark task for generat-ing musical passages in the audio
domain by using thedrum loops from the FreeSound Loop Dataset, which arepublicly re …

The voice generation task is to solve the problem of limited samples in the voice dataset
using computer technology. By increasing the number of samples, the accuracy of voice …

Creative rhythmic transformations of musical audio refer to automated methods for
manipulation of temporally-relevant sounds in time. This paper presents a method for joint …

In this paper we introduce StyleWaveGAN, a style-based drum sound generator that is a
variation of StyleGAN, a state-of-the-art image generator. By conditioning StyleWaveGAN on …

Influenced by the field of Computer Vision, Generative Adversarial Networks (GANs) are
often adopted for the audio domain using fixed-size two-dimensional spectrogram …

While generative adversarial networks (GANs) have been widely used in research on audio
generation, the training of a GAN model is known to be unstable, time consuming, and data …

The process of creating drum sounds has seen significant evolution in the past decades.
The development of analogue drum synthesizers, such as the TR-808, and modern sound …

Numerical emulations of the piano have been a subject of study since the early days of
sound synthesis. High-accuracy sound synthesis of acoustic instruments employs physical …