A music emotion recognition algorithm with hierarchical svm based classifiers

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

This paper proposes a music emotion recognition algorithm consisting of a kernel-based class separability (KBCS) feature selection method, a nonparametric weighted feature extraction (NWFE) feature extraction method, and a hierarchical support vector machines (SVMs) classifier to recognize four types of music emotion. For each music sample, a total of 35 features from dynamic, rhythm, pitch, and timbre of music were generated from music audio recordings. With the extracted features via feature selection and extraction methods, hierarchical SVM-based classifiers are then utilized to recognize four types of music emotion including happy, tensional, sad and peaceful. The performance of the proposed algorithm was evaluated by two datasets with a total of 219 classical music samples. In the first dataset, music emotion of each sample was annotated by recruited subjects, while the second dataset was labelled by music therapists. The two datasets were used to verify the perceived emotions from normal audience and music expert, respectively. The average accuracy of the proposed algorithm achieved at 86.94% and 92.33% for these two music datasets, respectively. The experimental results have successfully validated the effectiveness of the proposed music emotion recognition algorithm with hierarchical SVM-based classifiers.

Original languageEnglish
Title of host publicationProceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014
PublisherIEEE Computer Society
Pages1249-1252
Number of pages4
ISBN (Print)9781479952779
DOIs
Publication statusPublished - 2014 Jan 1
Event2nd International Symposium on Computer, Consumer and Control, IS3C 2014 - Taichung, Taiwan
Duration: 2014 Jun 102014 Jun 12

Publication series

NameProceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C 2014

Other

Other2nd International Symposium on Computer, Consumer and Control, IS3C 2014
CountryTaiwan
CityTaichung
Period14-06-1014-06-12

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering

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