Title
What Strikes The Strings Of Your Heart? - Multi-Label Dimensionality Reduction For Music Emotion Analysis
Keywords
Multi-emotion similarity preserving embedding; Multi-label dimensionality reduction; Music emotion analysis
Abstract
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.
Publication Date
11-3-2014
Publication Title
MM 2014 - Proceedings of the 2014 ACM Conference on Multimedia
Number of Pages
1069-1072
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1145/2647868.2655068
Copyright Status
Unknown
Socpus ID
84913530208 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84913530208
STARS Citation
Liu, Yang; Leu, Yan; Zhao, Yu; and Hua, Kien A., "What Strikes The Strings Of Your Heart? - Multi-Label Dimensionality Reduction For Music Emotion Analysis" (2014). Scopus Export 2010-2014. 8231.
https://stars.library.ucf.edu/scopus2010/8231