This research provides a comparative study of the genre classification performance of deep-
learning and traditional machine-learning models. Furthermore, we investigate the …

We introduce the Free Music Archive (FMA), an open and easily accessible dataset suitable
for evaluating several tasks in MIR, a field concerned with browsing, searching, and …

A decade has passed since the first review of research on a 'flagship application'of music
information retrieval (MIR): the problem of music genre recognition (MGR). During this time …

This chapter focuses on the recommendation problem in the music domain. Section 3.1
presents some common use cases in music recommendation. After that, Sect. 3.2, discusses …

Feature extraction is a crucial part of many MIR tasks. In this work, we present a system that
can automatically extract relevant features from audio for a given task. The feature extraction …

Social tags are free text labels that are applied to items such as artists, albums and songs.
Captured in these tags is a great deal of information that is highly relevant to Music …

The Music Information Retrieval Evaluation eXchange (MIREX) is the community-based
framework for the formal evaluation of Music Information Retrieval (MIR) systems and …

Given brief excerpts of commercially recorded music in one of ten broad genres of music,
participants in this study were asked to evaluate each excerpt and to assign it to one of the …

In this paper we present an approach to music genre classification which converts an audio
signal into spectrograms and extracts texture features from these time-frequency images …

The GTZAN dataset appears in at least 100 published works, and is the most-used public
dataset for evaluation in machine listening research for music genre recognition (MGR). Our …