Music emotion ranking

Content-based retrieval has emerged as a promising approach to information access. In this paper, we propose an approach to music emotion ranking. Specifically, we rank music in terms of arousal and valence and represent each song as a point in the 2D emotion space. Novel ranking-based methods for annotation, learning, and evaluation of music emotion recognition are developed and tested on a moderately large-scale database composed of 1240 pop songs. Results are provided to show the feasibility of the proposed approach.1

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: Yi-Hsuan Yang, Homer H. Chen
• Keywords: ICASSP 2009, Music Emotion, Music Emotion Ranking, Music Emotion Recognition, Signal Processing