|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||Music Genre Classification: A Semi-supervised Approach|
di, Baja GS
|Citation:||Poria S, Gelbukh A, Hussain A, Bandyopadhyay S & Howard N (2013) Music Genre Classification: A Semi-supervised Approach 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, Berlin Heidelberg: Springer. MCPR 2013 : 5th Mexican Conference on Pattern Recognition, 26.6.2013 - 29.6.2013, Queretaro, Mexico, pp. 254-263.|
|Series/Report no.:||Lecture Notes in Computer Science, 7914|
|Conference Name:||MCPR 2013 : 5th Mexican Conference on Pattern Recognition|
|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.|
|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|
|music_paper_formatted_for_MCPR_version_camera_ready_-_changed_AFG_(2).pdf||80.22 kB||Adobe PDF||View/Open|
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