Personalized music emotion recognition

In recent years, there has been a dramatic proliferation of research on information retrieval based on highly subjective concepts such as emotion, preference and aesthetic. Such retrieval methods are fascinating but challenging since it is difficult to built a general retrieval model that performs equally well to everyone. In this paper, we propose two novel methods, bag-of-users model and residual modeling, to accommodate the individual differences for emotion-based music retrieval. The proposed methods are intuitive and generally applicable to other information retrieval tasks that involve subjective perception. Evaluation result shows the effectiveness of the proposed methods. Categories and Subject Descriptors: H.3.3 Information Search and Retrieval: Retrieval Models; H.5.5 Sound and Music Computing: Systems, Modeling General Terms: Algorithms, Performance, Human Factors

• Type: Conference
• Year: 2009
• Where: SIGIR
• Authors: Yi-Hsuan Yang, Yu-Ching Lin, Homer H. Chen
• Keywords: Information Retrieval, Retrieval Models, SIGIR 2009, Such Retrieval Methods