Comparison of the statistical and information theory measures: Application to automatic musical genre classification

Machine Learning for Signal Processing 17 - Proceedings of the 2007 IEEE Signal Processing Society Workshop, MLSP

Volumn , Issue , 2007, Pages 241-246

  Ezzaidi, Hassan ^a   Rouat, Jean ^a,b  

^a UNIVERSITÉ DU QUÉBEC À CHICOUTIMI   (Canada)

^b UNIVERSITÉ DE SHERBROOKE   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUDIO ACOUSTICS; CYBERNETICS; DATABASE SYSTEMS; INFORMATION THEORY; LEARNING SYSTEMS; MAGNETOSTRICTIVE DEVICES; ROBOT LEARNING; SIGNAL PROCESSING; SPEECH RECOGNITION; STATISTICAL METHODS;

ADEQUATE MODELS; DECISION SPACES; DIVERGENCE MEASURE; GAUSSIAN MIXTURE MODEL; IEEE SIGNAL PROCESSING SOCIETY; INFORMATION MEASURES; MACHINE-LEARNING; MISMATCHED CONDITIONS; MUSIC GENRE CLASSIFICATION; MUSICAL GENRE CLASSIFICATION; REFERENCE SYSTEMS; SECOND ORDERS; SPEAKER RECOGNITION; STATISTICAL MODELLING; TESTING CASE;

CLASSIFICATION (OF INFORMATION);

EID: 48149102531     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2007.4414313     Document Type: Conference Paper

References (10)

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