Currently available reviews in the area of artificial intelligence-based music generation do
not provide a wide range of publications and are usually centered around comparing very …

Significant progress has been made in symbolic music generation with the help of deep
learning techniques. However, the tasks covered by symbolic music generation have not …

To apply neural sequence models such as the Transformers to music generation tasks, one
has to represent a piece of music by a sequence of tokens drawn from a finite set of pre …

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 …

Attention-based Transformer models have been increasingly employed for automatic music
generation. To condition the generation process of such a model with a user-specified …

Generating a complex work of art such as a musical composition requires exhibiting a
certain level of creativity. This depends on a variety of factors that are related to the hierarchy …

Generating music from text descriptions is a user-friendly mode since the text is a relatively
easy interface for user engagement. While some approaches utilize texts to control music …

Existing approaches for generating multitrack music with transformer models have been
limited in terms of the number of instruments, the length of the music segments and slow …

In this work, we propose a permutation invariant language model, SymphonyNet, as a
solution for symbolic symphony music generation. We propose a novel Multi-track Multi …

Recent progress in natural language processing has been adapted to the symbolic music
modality. Language models, such as Transformers, have been used with symbolic music for …