Generative artificial intelligence (AI) has emerged as a powerful technology with numerous
applications in various domains. There is a need to identify the requirements and evaluation …

This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

In this work, we propose DiffWave, a versatile diffusion probabilistic model for conditional
and unconditional waveform generation. The model is non-autoregressive, and converts the …

This paper introduces WaveGrad, a conditional model for waveform generation which
estimates gradients of the data density. The model is built on prior work on score matching …

We introduce Jukebox, a model that generates music with singing in the raw audio domain.
We tackle the long context of raw audio using a multiscale VQ-VAE to compress it to discrete …

Previous works (Donahue et al., 2018a; Engel et al., 2019a) have found that generating
coherent raw audio waveforms with GANs is challenging. In this paper, we show that it is …

Most generative models of audio directly generate samples in one of two domains: time or
frequency. While sufficient to express any signal, these representations are inefficient, as …

This workshop applies human centered themes to a new and powerful technology,
generative artificial intelligence (AI). Unlike AI systems that produce decisions or …

Generative adversarial networks have seen rapid development in recent years and have led
to remarkable improvements in generative modelling of images. However, their application …

The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …