DocumentCode :
2052412
Title :
Classification of pizzicato and sustained articulations
Author :
Hall, Glenn Eric ; Ezzaidi, Hassan ; Bahoura, Mohammed ; Volat, Christophe
Author_Institution :
Dept. of Appl. Sci., Univ. du Quebec a Chicoutimi, Chicoutimi, QC, Canada
fYear :
2013
fDate :
9-13 Sept. 2013
Firstpage :
1
Lastpage :
5
Abstract :
Musical instrument recognition has recently received growing attention from the research community and music industry. It plays a significant role in multimedia applications. Many approaches have been proposed to classify musical instruments. Particularly, the articulation refers to the style in which a song´s note is played. In this paper, we propose a new avenue for musical instrument classification into two categories: Pizzicato and Sustain articulations. New features derived from chromagram contours are investigated by using the classical invariant moments. A comparison with a reference system using a feature vector constructed from 38 feature parameters and using k-NN classifier is provided. The standard RWC database is used for all experiments.
Keywords :
audio databases; music; musical instruments; pattern classification; chromagram contours; classical invariant moments; feature vector; k-NN classifier; music industry; musical instrument classification; musical instrument recognition; pizzicato classification; standard RWC database; sustained articulations; Databases; Feature extraction; Instruments; Shape; Timbre; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
Conference_Location :
Marrakech
Type :
conf
Filename :
6811404
Link To Document :
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