Please use this identifier to cite or link to this item:
|Title:||A hierarchical approach for music chord modeling based on the analysis of tonal characteristics|
|Source:||Maddage, N.C., Kankanhalli, M.S., Li, H. (2006). A hierarchical approach for music chord modeling based on the analysis of tonal characteristics. 2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings 2006 : 945-948. ScholarBank@NUS Repository. https://doi.org/10.1109/ICME.2006.262676|
|Abstract:||This paper first discusses how the signal segmentation and tonal characteristics of music notes effect in music chord detection. Two approaches, pitch class profile approach and psycho-acoustical approach, which differently represent these tonal characteristics, are examined for chord detection. The analysis of the tonal characteristics reveals that not only the fundamental frequency of music note but also its harmonics and sub-harmonies in different octaves contribute for detecting related music chord. A hierarchical approach, which transforms the music chord tonal characteristics in each octave onto probabilistic space, is then proposed for modeling the music chord. Our experimental results show that detection of chord type, Major, Minor, Diminish, and Augmented, and individual chords, 12 chords per chord type, are improved with the proposed hierarchical chord modeling approach. Experimental results also reveal that the tempo proportional signal segmentation is more effective extracting tonal characteristics than using fixed length segmentation. © 2006 IEEE.|
|Source Title:||2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.