DocumentCode
2052945
Title
Pitch Oriented Automatic Singer Identification in Pop Music
Author
Chang, Peichen
Author_Institution
Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA
fYear
2009
fDate
14-16 Sept. 2009
Firstpage
161
Lastpage
166
Abstract
In this paper, we proposed two novel methods used to distinguish the singer of a pop music. We focused on a single singer and single track case. These two methods are ldquoPitch Extractionrdquo method and ldquo1/12 OFCCrdquo method. The Pitch Extraction method is composed of three stages and they are Singing pitch estimation stage, Exact pitch calculation stage and GMM classification stage. ldquo1/12 OFCCrdquo method is composed of ldquoPitch Feature Calculationrdquo and GMM classification. We also compare these two methods with OFCC based method. With ldquoPitch Extractionrdquo and ldquo1/12 OFCCrdquo method, we have some improvement on works of singer identification using single feature.
Keywords
music; speaker recognition; automatic singer identification; pitch calculation; pitch extraction; pitch feature calculation; pop music; singing pitch estimation; Cepstrum; Data mining; Hidden Markov models; Human voice; Information filtering; Information filters; Instruments; Interference; Mel frequency cepstral coefficient; USA Councils; GMM; pitch; singer identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Computing, 2009. ICSC '09. IEEE International Conference on
Conference_Location
Berkeley, CA
Print_ISBN
978-1-4244-4962-0
Electronic_ISBN
978-0-7695-3800-6
Type
conf
DOI
10.1109/ICSC.2009.28
Filename
5298607
Link To Document