Building a Personalized Music Emotion Prediction System

With the development of multimedia technology, research on music is getting more and more popular. Nowadays researchers focus on studying the relationship between music and listeners’ emotions but they didn’t consider users’ differences. Therefore, we propose a Personalized Music Emotion Prediction (P-MEP) System to assist predicting listeners’ music emotion concerning with users’ differences. To analyze listeners’ emotional response to music, the P-MEP rules will be generated in the analysis procedure consisting of 5 phases. During the application procedure, the P-MEP System predicts the new listener’s emotional response to music. The result of the experiment shows that the generated P-MEP rules can be used to predict emotional response to music concerning with listeners’ differences.

[1]  Isabelle Peretz,et al.  ception and Performance, 26, 1797–1813. Juslin, PN, & Sloboda, JA (2001). Music and emotion: Theory and re-search. New York: Oxford Univer , 2002 .

[2]  Zhang Naiyao,et al.  User-adaptive music emotion recognition , 2004, Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004..

[3]  Markus Koppenberger,et al.  Content-based music audio recommendation , 2005, ACM Multimedia.

[4]  Jia-Ling Koh,et al.  Efficient Feature Mining in Music Objects , 2001, DEXA.

[5]  Sudipto Guha,et al.  ROCK: a robust clustering algorithm for categorical attributes , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[6]  Arbee L. P. Chen,et al.  Music Classification Using Significant Repeating Patterns , 2004, DASFAA.

[7]  Shogo Nishida,et al.  Content-based filtering system for music data , 2004, 2004 International Symposium on Applications and the Internet Workshops. 2004 Workshops..

[8]  W. S. Reilly,et al.  Believable Social and Emotional Agents. , 1996 .

[9]  Tao Li,et al.  Music genre classification with taxonomy , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[10]  Man-Kwan Shan,et al.  A personalized music filtering system based on melody style classification , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[11]  Phil Winsor.  Automated Music Composition , 1989 .

[12]  Arbee L. P. Chen,et al.  Efficient kNN search in polyphonic music databases using a lower bounding mechanism , 2005, MIR '03.

[13]  Man-Kwan Shan,et al.  Music style mining and classification by melody , 2002, Proceedings. IEEE International Conference on Multimedia and Expo.

[14]  Namunu Chinthaka Maddage.  Automatic structure detection for popular music , 2006, IEEE Multimedia.

[15]  Arbee L. P. Chen,et al.  An Efficient Approach to Extracting Approximate Repeating Patterns in Music Databases , 2005, DASFAA.

[16]  Arbee L. P. Chen,et al.  Music segmentation by rhythmic features and melodic shapes , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[17]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[18]  Barry Vercoe,et al.  Folk Music Classification Using Hidden Markov Models , 2001 .

[19]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[20]  Arbee L. P. Chen,et al.  Efficient K-NN search in polyphonic music databases using a lower bounding mechanism , 2003, Multimedia Information Retrieval.

[21]  Suh-Yin Lee,et al.  Emotion-based music recommendation by association discovery from film music , 2005, MULTIMEDIA '05.

[22]  Man-Kwan Shan,et al.  Looking for new, not known music only: music retrieval by melody style , 2004, Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004..

[23]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[24]  J. Sloboda,et al.  Music and emotion: Theory and research , 2001 .

[25]  Jean-Gabriel Ganascia,et al.  Pattern Detection and Discovery: The Case of Music Data Mining , 2002, Pattern Detection and Discovery.

[26]  Arbee L. P. Chen,et al.  A Music Recommendation System Based on Music and User Grouping , 2005, Journal of Intelligent Information Systems.

[27]  Yueting Zhuang,et al.  Popular music retrieval by detecting mood , 2003, SIGIR.

[28]  Mohan S. Kankanhalli,et al.  Content-based music structure analysis with applications to music semantics understanding , 2004, MULTIMEDIA '04.

[29]  R. Thayer.  The biopsychology of mood and arousal , 1989 .

[30]  Lie Lu,et al.  Automatic mood detection and tracking of music audio signals , 2006, IEEE Transactions on Audio, Speech, and Language Processing.