Improving automatic music classification performance by extracting features from different types of data

MIR 2010 - Proceedings of the 2010 ACM SIGMM International Conference on Multimedia Information Retrieval

Volumn , Issue , 2010, Pages 257-266

  McKay, Cory ^a   Fujinaga, Ichiro ^a  

^a MCGILL UNIVERSITY   (Canada)

Author keywords

Automatic music classification; Features; Genre; Machine learning; Multi modal; Music information retrieval

Indexed keywords

CLASSIFICATION ACCURACY; DATA SOURCE; EXTRACTING FEATURES; FEATURE TYPES; HIGH-LEVEL FEATURES; MACHINE-LEARNING; MISCLASSIFICATIONS; MULTI-MODAL; MUSIC CLASSIFICATION; MUSIC INFORMATION RETRIEVAL; MUSICAL GENRE CLASSIFICATION; MUSICAL INFORMATION; OPEN-SOURCE SOFTWARES; RESEARCH DIRECTIONS; SYMBOLIC DATA; TOOLSETS;

AUDIO ACOUSTICS; ELECTRONIC MUSICAL INSTRUMENTS; EXPERIMENTS; FEATURE EXTRACTION; INFORMATION RETRIEVAL; LEARNING SYSTEMS;

CLASSIFICATION (OF INFORMATION);

EID: 77952348847     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1743384.1743430     Document Type: Conference Paper

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