Music structure analysis (MSA) methods traditionally search for musically meaningful
patterns in audio: homogeneity, repetition, novelty, and segment-length regularity. Hand …

The analysis of the structure of musical pieces is a task that remains a challenge for Artificial
Intelligence, especially in the field of Deep Learning. It requires prior identification of …

Recently, the field of musical co-creativity has gained some momentum. In this context, our
goal is twofold: to develop an intelligent listening and predictive module of chord sequences …

Music structure estimation has recently emerged as a central topic within the field of music
information retrieval. Indeed, as music is a highly structured information stream, knowledge …

Recent researches on Automatic Chord Extraction (ACE) have focused on the improvement
of models based on machine learning. However, most models still fail to take into account …

In this paper, we propose a method called temporal correlation support vector machine
(TCSVM) for automatic major-minor chord recognition in audio music. We first use robust …

Digital audio processing tools offer music researchers the opportunity to examine both non-
notated music and music as performance. This chapter summarises the types of information …

In recent decades, rapid technological advances have resulted in a huge quantity of readily
accessible digital musical recordings. The scope of large corpora presents difficulties for …

In recent years, complex convolutional neural network architectures such as the Inception
architecture have been shown to offer significant improvements over previous architectures …

Abstract Automatic Chord Estimation (ACE) is a fundamental task in Music Information
Retrieval (MIR) and has applications in both music performance and MIR research. The task …