This paper focuses on emotion recognition and understanding in Contemporary Western music. The study seeks to investigate the relationship between perceived emotion and musical features in the fore-mentioned musical genre. A set of 27 Contemporary music excerpts is used as stimuli to gather responses from both musicians and non-musicians which are then mapped on an emotional plane in terms of arousal and valence dimensions. Audio signal analysis techniques are applied to the corpus and a base feature set is obtained. The feature set contains characteristics ranging from low-level spectral and temporal acoustic features to high-level contextual features. The feature extraction process is discussed with particular emphasis on the interaction between acoustical and structural parameters. Statistical relations between audio features and emotional ratings from psychological experiments are systematically investigated. Finally, a linear model is created using the best features and the mean ratings and its prediction efficiency is evaluated and discussed.
|Published - 2011
|8th Sound and Music Computing Conference, SMC 2011 - Padova, Italy
Duration: Jul 6 2011 → Jul 9 2011
|8th Sound and Music Computing Conference, SMC 2011
|7/6/11 → 7/9/11
ASJC Scopus subject areas
- General Computer Science