TY - GEN
T1 - Music emotion retrieval based on acoustic features
AU - Deng, James Jie
AU - LEUNG, Clement H C
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012
Y1 - 2012
N2 - Music emotion expresses inherent and high-level states of mind and spiritual quality. In this paper, a hierarchical framework is proposed, which consists of two layers: an external layer that represents preliminary and superficial emotions and an inherent layer that represents psychic and resonant emotions. Using these two layers, a Resonance-Arousal-Valence (RAV) emotion model has been constructed. Five feature sets, including intensity, timbre, rhythm, pitch and tonality, and harmony, are extracted to represent music emotions in the RAV model. In order to effectively represent emotions with extracted features, suitable weighting schemes are utilized to balance the different features. As each music clip may have rather complex emotions, a supervised multiclass label model is adopted to annotate emotions with emotion multinomial. Preliminary experimental results indicate that the proposed emotion model and retrieval approach is able to deliver good retrieval performance.
AB - Music emotion expresses inherent and high-level states of mind and spiritual quality. In this paper, a hierarchical framework is proposed, which consists of two layers: an external layer that represents preliminary and superficial emotions and an inherent layer that represents psychic and resonant emotions. Using these two layers, a Resonance-Arousal-Valence (RAV) emotion model has been constructed. Five feature sets, including intensity, timbre, rhythm, pitch and tonality, and harmony, are extracted to represent music emotions in the RAV model. In order to effectively represent emotions with extracted features, suitable weighting schemes are utilized to balance the different features. As each music clip may have rather complex emotions, a supervised multiclass label model is adopted to annotate emotions with emotion multinomial. Preliminary experimental results indicate that the proposed emotion model and retrieval approach is able to deliver good retrieval performance.
KW - arousal
KW - Music emotion
KW - music emotion retrieval
KW - resonance
KW - valence
UR - http://www.scopus.com/inward/record.url?scp=84858659079&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-28744-2_22
DO - 10.1007/978-3-642-28744-2_22
M3 - Conference contribution
AN - SCOPUS:84858659079
SN - 9783642287435
T3 - Lecture Notes in Electrical Engineering
SP - 169
EP - 177
BT - Advances in Electric and Electronics
T2 - 2012 2nd International Conference on Electric and Electronics, EEIC 2012
Y2 - 21 April 2012 through 22 April 2012
ER -