What strikes the strings of your heart? - Multi-label dimensionality reduction for music emotion analysis

Yan Liu, Yan Leu, Yu Zhao, Kien A. Hua

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)


Music can convey and evoke powerful emotions. This amazing ability has fascinated the general public and also attracted the researchers from different fields to discover the relationship between music and emotion. Psychologists have indicated that some specific characters of rhythm, harmony, melody, and also their combinations can evoke certain kinds of emotions. Their hypotheses are based on real life experience and proved by psychological paradigms on human beings. Aiming at the same target, this paper intends to design a systematic and quantitative framework, and answer three widely interested questions: 1) what are the intrinsic features embedded in music signal that essentially evoke human emotions; 2) to what extent these features influence human emotions; and 3) whether the findings from computational models are consistent with the existing research results from psychological experiments. We formulate the problem as a multi-label dimensionality reduction problem and provide the optimal solution. The proposed multi-emotion similarity preserving embedding technique not only shows better performance in two standard music emotion datasets but also demonstrates some interesting observations for further research in this interdisciplinary topic.
Original languageEnglish
Title of host publicationMM 2014 - Proceedings of the 2014 ACM Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Number of pages4
ISBN (Electronic)9781450330633
Publication statusPublished - 1 Jan 2014
Event2014 ACM Conference on Multimedia, MM 2014 - Orlando, United States
Duration: 3 Nov 20147 Nov 2014


Conference2014 ACM Conference on Multimedia, MM 2014
Country/TerritoryUnited States


  • Multi-emotion similarity preserving embedding
  • Multi-label dimensionality reduction
  • Music emotion analysis

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Media Technology
  • Software


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