DocumentCode :
259653
Title :
Supervised Music Chord Recognition
Author :
Rida, Imad ; Herault, Romain ; Gasso, Gilles
Author_Institution :
INSA de Rouen, Normandie Univ., St. Étienne-du-Rouvray, France
fYear :
2014
fDate :
3-6 Dec. 2014
Firstpage :
336
Lastpage :
341
Abstract :
Chord represents the back-bone of occidental music genre as it contains rich harmonic information which is useful for various music applications such as music genre classification or music retrieval. Hence, chord recognition or transcription is of importance for music representation. In this paper we focus on chord recognition and especially investigate different features representation used in such a system: classical features as well as a new type of feature we propose are explored. We evaluate their usefulness through a multi-class chord classification problem.
Keywords :
music; feature representation; harmonic information; multiclass chord classification; music representation; music retrieval; occidental music genre classification; supervised music chord recognition; Feature extraction; Harmonic analysis; Hidden Markov models; Kernel; Spectrogram; Training; Vectors; Music; chord; feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2014 13th International Conference on
Conference_Location :
Detroit, MI
Type :
conf
DOI :
10.1109/ICMLA.2014.60
Filename :
7033137
Link To Document :
بازگشت