Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/20596
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Peer Review Status: Refereed
Authors: Poria, Soujanya
Gelbukh, Alexander
Hussain, Amir
Bandyopadhyay, Sivaji
Howard, Newton
Contact Email: amir.hussain@stir.ac.uk
Title: Music Genre Classification: A Semi-supervised Approach
Editors: Carrasco-Ochoa, JA
Martinez-Trinidad, JF
Rodriguez, JS
di, Baja GS
Citation: Poria S, Gelbukh A, Hussain A, Bandyopadhyay S & Howard N (2013) Music Genre Classification: A Semi-supervised Approach, Carrasco-Ochoa JA, Martinez-Trinidad JF, Rodriguez JS, di Baja GS (ed.) Pattern Recognition: 5th Mexican Conference, MCPR 2013, Querétaro, Mexico, June 26-29, 2013. Proceedings, MCPR 2013 : 5th Mexican Conference on Pattern Recognition, Queretaro, Mexico, 26.6.2013 - 29.6.2013, Berlin Heidelberg: Springer, pp. 254-263.
Issue Date: 2013
Series/Report no.: Lecture Notes in Computer Science, 7914
Conference Name: MCPR 2013 : 5th Mexican Conference on Pattern Recognition
Conference Dates: 2013-06-26T00:00:00Z
Conference Location: Queretaro, Mexico
Abstract: Music genres can be seen as categorical descriptions used to classify music basing on various characteristics such as instrumentation, pitch, rhythmic structure, and harmonic contents. Automatic music genre classification is important for music retrieval in large music collections on the web. We build a classifier that learns from very few labeled examples plus a large quantity of unlabeled data, and show that our methodology outperforms existing supervised and unsupervised approaches. We also identify salient features useful for music genre classification. We achieve 97.1% accuracy of 10-way classification on real-world audio collections.
Type: Conference Paper
Status: Book Chapter: publisher version
Rights: Publisher policy allows this work to be made available in this repository; Published in Carrasco-Ochoa JA, Martinez-Trinidad JF, Rodriguez JS, di Baja GS (ed.) Pattern Recognition: 5th Mexican Conference, MCPR 2013, Querétaro, Mexico, June 26-29, 2013. Proceedings, MCPR 2013 : 5th Mexican Conference on Pattern Recognition, Queretaro, Mexico, 26.6.2013 - 29.6.2013, Berlin Heidelberg: Springer, pp. 254-263. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38989-4_26
URI: http://hdl.handle.net/1893/20596
URL: http://link.springer.com/chapter/10.1007/978-3-642-38989-4_26#
Affiliation: Jadavpur University
National Polytechnic Institute
Computing Science - CSM Dept
Jadavpur University
Massachusetts Institute of Technology

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