Within the vast expanse of computerized language processing, a revolutionary entity known
as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to …

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 …

In pop music, accompaniments are usually played by multiple instruments (tracks) such as
drum, bass, string and guitar, and can make a song more expressive and contagious by …

Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors
from computers. One of its most prolific subfields is that of Music Generation (also called …

Generative artificial intelligence (GenAI) is rapidly becoming a viable tool to enhance
productivity and act as a catalyst for innovation across various sectors. Its ability to perform …

Various disconnected chord datasets are currently available for music analysis and
information retrieval, but they are often limited by either their size, non-openness, lack of …