DocumentCode :
1947849
Title :
Signal processing for segmentation of vocal and non-vocal regions in songs: A review
Author :
Bonjyotsna, A. ; Bhuyan, M.
Author_Institution :
Deptt. of Electron. & Commun. Eng., Tezpur Univ., Tezpur, India
fYear :
2013
fDate :
7-8 Feb. 2013
Firstpage :
87
Lastpage :
91
Abstract :
It has been of great importance to us to identify a singer in a song or from collection of songs. Speaker identification is being widely used in organizing, browsing and retrieving music collections, and its speech processing techniques are well established. But the inability to delete the background accompaniment fully has set a limitation in extracting singing voice features appropriately. Singing voice identification is basically done on the basis of three techniques viz. locating vocal/non-vocal segment from the song, feature extraction of the vocal segment and statistical classification. This paper attempts to review on the various techniques developed for detection of vocal/non-vocal segments and tries to find out scope of improvement to formulate a generalized vocal detection technique.
Keywords :
feature extraction; music; signal classification; signal detection; statistical analysis; background accompaniment; feature extraction; generalized vocal detection technique; music collection browsing; music collection organization; music collection retrieval; nonvocal region segmentation; signal processing; singing voice feature; singing voice identification; song collection; statistical classification; vocal region segmentation; Acoustics; Hidden Markov models; Signal to noise ratio;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Image Processing & Pattern Recognition (ICSIPR), 2013 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4673-4861-4
Type :
conf
DOI :
10.1109/ICSIPR.2013.6497965
Filename :
6497965
Link To Document :
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