Music retrieval in joint emotion space using audio features and emotional tags

James J. Deng, Clement H C LEUNG

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Emotion-based music retrieval provides a natural and humanized way to help people experience music. In this paper, we utilize the three-dimensional Resonance-Arousal-Valence emotion model to represent the emotions invoked by music, and the relationship between acoustic features and their emotional impact based on this model is established. In addition, we also consider the emotional tag features for music, and then represent acoustic features and emotional tag features jointly in a low dimensional embedding space for music emotion, while the joint emotion space is optimized by minimizing the joint loss of acoustic features and emotional tag features through dimension reduction. Finally we construct a unified framework for music retrieval in joint emotion space by the means of query-by-music or query-by-tag or together, and then we utilize our proposed ranking algorithm to return an optimized ranked list that has the highest emotional similarity. The experimental results show that the joint emotion space and unified framework can produce satisfying results for emotion-based music retrieval.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 19th International Conference, MMM 2013, Proceedings
Pages524-534
Number of pages11
EditionPART 1
DOIs
Publication statusPublished - 2013
Event19th International Conference on Advances in Multimedia Modeling, MMM 2013 - Huangshan, China
Duration: 7 Jan 20139 Jan 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7732 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Advances in Multimedia Modeling, MMM 2013
Country/TerritoryChina
CityHuangshan
Period7/01/139/01/13

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Audio features
  • Dimensionality reduction
  • Emotional tag
  • Music emotion
  • Music retrieval
  • Ranking

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