Název:	Set of texture descriptors for music genre classification
Autoři:	Nanni, Loris Costa, Yandre Brahnam, Sheryl
Citace zdrojového dokumentu:	WSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 145-152.
Datum vydání:	2014
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	konferenční příspěvek conferenceObject
URI:	wscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf http://hdl.handle.net/11025/26409
ISBN:	978-80-86943-71-8
Klíčová slova:	hudební žánr;struktura;zpracování obrazu;rozpoznání vzorů
Klíčová slova v dalším jazyce:	music genre;texture;image processing;pattern recognition
Abstrakt v dalším jazyce:	This paper presents a comparison among different texture descriptors and ensembles of descriptors for music genre classification. The features are extracted from the spectrogram calculated starting from the audio signal. The best results are obtained by extracting features from subwindows taken from the entire spectrogram by Mel scale zoning. To assess the performance of our method, two different databases are used: the Latin Music Database (LMD) and the ISMIR 2004 database. The best descriptors proposed in this work greatly outperform previous results using texture descriptors on both databases: we obtain 86.1% accuracy with LMD and 82.9% accuracy with ISMIR 2004. Our descriptors and the MATLAB code for all experiments reported in this paper will be available at https://www.dei.unipd.it/node/2357 .
Práva:	@ Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2014: Communication Papers Proceedings

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