Work

Multi-Label Classification Of Music Into Emotions.

Year: 2008

Type: article

Abstract: In this paper, the automated detection of emotion in music is modeled as a multilabel classification task, where a piece of music may belong to more than one class. Four algorithms are evaluated and compared in this task. Furthermore, the predictive power of several audio features is evaluated using a new multilabel feature selection method. Experiments are conducted on a set of 593 songs with 6 clusters of music emotions based on the Tellegen-Watson-Clark model. Results provide interesting insights into the quality of the discussed algorithms and features.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.1414899

Authors: Trohidis, Konstantinos, Tsoumakas, Grigorios, Kalliris, George, Vlahavas, Ioannis P.

Institution: Aristotle University of Thessaloniki

Language: English

Topic: Music and Audio Processing

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2165766797

FWCI: 35.06

Cites: 21

Cited by: 648

Related to: 10