Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICPR.2004.1334225
Title: Singer identification based on vocal and instrumental models
Authors: Maddage, N.C.
Xu, C.
Wang, Ye. 
Issue Date: 2004
Source: Maddage, N.C., Xu, C., Wang, Ye. (2004). Singer identification based on vocal and instrumental models. Proceedings - International Conference on Pattern Recognition 2 : 375-378. ScholarBank@NUS Repository. https://doi.org/10.1109/ICPR.2004.1334225
Abstract: In this paper, we propose a novel method to identify the singer of a query song from the audio database. The database contains over 100 popular songs of solo singers. The rhythm structure of the song is analyzed using our proposed rhythm tracking method and the song is segmented into beat space time frames, where within the beat space time length the harmonic structure is quasi stationary. This inter-beat time resolution of the song is used for both feature extraction and training of the classifiers (i.e. Support Vector Machine (SVM) for vocal/instrumental boundary detection and Gaussian Mixture Models (GMMs) for modeling the singer). Combining the instrumental music similarities in the songs of the same singer with the vocal model can improve the identification of the singer with an accuracy of over 87%.
Source Title: Proceedings - International Conference on Pattern Recognition
URI: http://scholarbank.nus.edu.sg/handle/10635/39956
ISBN: 0769521282
ISSN: 10514651
DOI: 10.1109/ICPR.2004.1334225
Appears in Collections:Staff Publications

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