A novel framework for efficient automated singer identification in large music databases

ACM Transactions on Information Systems

Volumn 27, Issue 3, 2009, Pages

  Shen, Jialie ^a   Shepherd, John ^b   Cui, Bin ^c   Tan, Kian Lee ^d  

^a SINGAPORE MANAGEMENT UNIVERSITY   (Singapore)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

^c PEKING UNIVERSITY   (China)

^d NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Classification; EM algorithm; Evaluation; Gaussian mixture models; Music retrieval; Singer identification; Statistical modeling

Indexed keywords

CONTENT-BASED MUSIC RETRIEVAL; EM ALGORITHMS; EXPERIMENTAL STUDIES; EXPLOSIVE GROWTH; GAUSSIAN MIXTURE MODEL; HYBRID ARCHITECTURES; IDENTIFICATION PROCESS; LOW-LEVEL FEATURES; MIXTURE MODEL; MULTIMEDIA DATA; MULTIMEDIA DATABASE; MUSIC DATA; MUSIC DATABASE; MUSIC RETRIEVAL; MUSIC SEGMENTS; MUSICAL PIECES; STATE-OF-THE-ART APPROACH; STATISTICAL MODELING;

COMMUNICATION CHANNELS (INFORMATION THEORY); DATABASE SYSTEMS; INFORMATION SERVICES; MIXTURES; SCALABILITY;

COMPUTER MUSIC;

EID: 75649095708     PISSN: 10468188     EISSN: 15582868     Source Type: Journal    
DOI: 10.1145/1508850.1508856     Document Type: Article

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