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 …

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 …

This paper presents the Jazz Transformer, a generative model that utilizes a neural
sequence model called the Transformer-XL for modeling lead sheets of Jazz music …

Automatically inferring the structural properties of raw multimedia documents is essential in
today's digitized society. Given its hierarchical and multi-faceted organization, musical …

The automatic extraction of structural information from music recordings constitutes a central
research topic. In this paper, we deal with a subproblem of audio structure analysis called …

Research on music generation using deep learning has attracted more attention; in
particular, Transformer-based models have succeeded in generating coherent musical …

The development of automated methods for revealing the repetitive structure of a given
music recording is of central importance in music information retrieval. In this paper, we …

The Transformer model has gained popularity because of its capabilities for solving multiple
tasks. One of them is automatic music generation. Many studies have proven that this model …

This paper addresses the novel task of detecting chorus sections in English and Japanese
lyrics text. Although chorus-section detection using audio signals has been studied, whether …

In this paper, we propose a new representation as input of a Convolutional Neural Network
with the goal of estimating music structure boundaries. For this task, previous works used a …