With recent advances in the field of music informatics, approaches to audio-based music
structural analysis have matured considerably, allowing researchers to reassess the …

Deep learning methods are recognised as state-of-the-art for many applications of machine
learning. Recently, deep learning methods have emerged as a solution to the task of …

Music information retrieval (MIR) is “a multidisciplinary research endeavor that strives to
develop innovative content‐based searching schemes, novel interfaces, and evolving …

According to musicological studies on oral transmission, repeated patterns are considered
important for determining musical similarity in folk songs. In this paper, we study the …

Repetition is a basic indicator of musical structure. This study introduces new algorithms for
identifying musical phrases based on repetition. Phrases combine to form sections yielding …

Nowadays computers play an important role in all areas of music, from composition to
production and live performance. This is obvious for all kinds of popular music, where …

There have been many attempts to model the ability of human musicians to take a score and
perform or render it expressively, by adding tempo, timing, loudness and articulation …

This paper presents a method for discovering patterns of note collections that repeatedly
occur in a piece of music. We assume occurrences of these patterns must appear at least …

Algorithms for the discovery of musical repetition have been developed in audio and
symbolic domains more or less independently for over a decade. In this paper we combine …

COSIATEC, SIATECCompress and Forth's algorithm are point-set compression algorithms
developed for discovering repeated patterns in music, such as themes and motives that …