Emotion-based Music Analysis and Beyond

Updated: 3:28pm, 8 Nov, 2022
2 February 2016 (Tue)
Room 101, 1/F., Runme Shaw Bldg., HKU
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Automatic recognition of the perceived emotion of music allows users to retrieve and organize their music collections in a fashion that is content-centric and intuitive. A typical approach to music emotion recognition categorizes emotions into a number of classes and applies machine learning techniques to train a classifier. This approach, however, faces a granularity issue that the number of emotion classes is too small in comparison with the richness of emotion perceived by humans. In this talk, I would introduce some research that takes a very different perspective and views emotions as points in a 2-D space spanned by two latent dimensions: valence (how positive or negative) and arousal (how exciting or calming). In this approach, music emotion recognition becomes the prediction of the valence and arousal values of a song corresponding to a point in the emotion plane. This way, the granularity and ambiguity issues associated with emotion classes no longer exist since no categorical class is needed. Moreover, because the 2D plane provides a simple means for user interface, new emotion-based music organization, browsing, and retrieval can be easily created for mobile devices that have small display area.

About the speaker(s):

<p>Yi-Hsuan Yang is an Associate Research Fellow with Academia Sinica. He received his Ph.D. degree in Communication Engineering from National Taiwan University in 2010, and became an Assistant Research Fellow in Academia Sinica in 2011. He is also an Adjunct Associate Professor with the National Tsing Hua University, Taiwan. His research interests include music information retrieval, machine learning and affective computing. Dr. Yang was a recipient of the 2011 IEEE Signal Processing Society (SPS) Young Author Best Paper Award, the 2012 ACM Multimedia Grand Challenge First Prize, and the 2014 Ta-You Wu Memorial Research Award of the Ministry of Science and Technology, Taiwan. He is an author of the book Music Emotion Recognition (CRC Press 2011) and a tutorial speaker on music affect recognition in the International Society for Music Information Retrieval Conference (ISMIR 2012). In 2014, he served as a Technical Program Co-chair of ISMIR, and a Guest Editor of the IEEE Transactions on Affective Computing and the ACM Transactions on Intelligent Systems and Technology.<br /><br /></p>

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