DocumentCode :
1783872
Title :
Melody Extraction for Vocal Polyphonic Music Based on Bayesian Framework
Author :
Liming Song ; Ming Li ; Yonghong Yan
Author_Institution :
Key Lab. of Speech Acoust. & Content Understanding, Inst. of Acoust., Beijing, China
fYear :
2014
fDate :
27-29 Aug. 2014
Firstpage :
570
Lastpage :
573
Abstract :
In order to automatically extract the main melody contours from polyphonic music especially vocal melody songs, we present an effective approach based on a Bayesian framework. According to various information from the music signals, we use a pitch evolution model describing how pitch contour changes and an acoustic model representing the acoustic characteristics when the pitch is a hypothesized one, and obtain the optimal melody contour utilizing a Viterbi algorithm. The experimental results on the RWC popular music database indicate that the overall accuracy achieves 73.4%.
Keywords :
Bayes methods; acoustic signal processing; audio databases; feature extraction; information retrieval; music; Bayesian framework; RWC popular music database; Viterbi algorithm; acoustic model; automatic main melody contour extraction; music signals; optimal melody contour; pitch contour; pitch evolution model; vocal melody songs; vocal polyphonic music; Harmonic analysis; Instruments; Multiple signal classification; Music; Speech; Speech processing; Bayesian framework; Viterbi algorithm; melody extraction; polyphonic music;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2014 Tenth International Conference on
Conference_Location :
Kitakyushu
Print_ISBN :
978-1-4799-5389-9
Type :
conf
DOI :
10.1109/IIH-MSP.2014.147
Filename :
6998393
Link To Document :
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