| Title: | Set of texture descriptors for music genre classification |
| Authors: | Nanni, Loris Costa, Yandre Brahnam, Sheryl |
| Citation: | 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. |
| Issue Date: | 2014 |
| Publisher: | Václav Skala - UNION Agency |
| Document type: | konferenční příspěvek conferenceObject |
| URI: | wscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf http://hdl.handle.net/11025/26409 |
| ISBN: | 978-80-86943-71-8 |
| Keywords: | hudební žánr;struktura;zpracování obrazu;rozpoznání vzorů |
| Keywords in different language: | music genre;texture;image processing;pattern recognition |
| Abstract in different language: | 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 . |
| Rights: | @ Václav Skala - UNION Agency |
| Appears in Collections: | WSCG 2014: Communication Papers Proceedings |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/26409Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.