https://scholars.lib.ntu.edu.tw/handle/123456789/636449
標題: | Personalized music emotion recognition via model adaptation | 作者: | Wang, Ju Chiang YI-HSUAN YANG Wang, Hsin Min SHYH-KANG JENG |
公開日期: | 1-十二月-2012 | 來源出版物: | 2012 Conference Handbook - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2012 | 摘要: | In the music information retrieval (MIR) research, developing a computational model that comprehends the affective content of music signal and utilizes such a model to organize music collections have been an essential topic. Emotion perception in music is in nature subjective. Consequently, building a general emotion recognition system that performs equally well for every user could be insufficient. In contrast, it would be more desirable for one's personal computer/device being able to understand his/her perception of music emotion. In our previous work, we have developed the acoustic emotion Gaussians (AEG) model, which can learn the broad emotion perception of music from general users. Such a general music emotion model, called the background AEG model in this paper, can recognize the perceived emotion of unseen music from a general point of view. In this paper, we go one step further to realize the personalized music emotion modeling by adapting the background AEG model with a limited number of emotion annotations provided by a target user in an online and dynamic fashion. A novel maximum a posteriori (MAP)-based algorithm is proposed to achieve this in a probabilistic framework. We carry out quantitative evaluations on a well-known emotion annotated corpus, MER60, to validate the effectiveness of the proposed method for personalized music emotion recognition. © 2012 APSIPA. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/636449 | ISBN: | 9780615700502 |
顯示於: | 電機工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。