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A Survey on: Sound Source Separation Methods

Ms. Monali R. Pimpale, Prof. Shanthi Therese , Prof. Vinayak Shinde,, ,
Department of Computer Engineering, Mumbai University, Shree L.R. Tiwari College of Engineering and Technology,Mira Road, India.
:under process

now a day’s multimedia databases are growing rapidly on large scale. For the effective management and exploration of large amount of music data the technology of singer identification is developed. With the help of this technology songs performed by particular singer can be clustered automatically. To improve the Performance of singer identification the technologies are emerged that can separate the singing voice from music accompaniment. One of the methods used for separating the singing voice from music accompaniment is non-negative matrix partial co factorization. This paper studies the different techniques for separation of singing voice from music accompaniment.

Monali R. Pimpale," A Survey on: Sound Source Separation Methods”, International Journal of Computer Engineering In Research Trends, 3(11):580-584,November-2016

Keywords : singer identification, non-negative matrix partial co factorization

[1] Tuomas Virtanen ,”Unsupervised Learning Methods for Source Separation in Monaural Music Signals” Tuomas Virtanen

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[9] Ying Hu and Guizhong Liu, “Separation of Singing Voice Using Nonnegative Matrix Partial CoFactorization for Singer Identification”, IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 23, no. 4, pp. 643 – 653, April 2015.   
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[14] Virtanen, Tuomas. "Separation of sound sources by convolutive sparse coding." ISCA Tutorial and Researc Workshop (ITRW) on Statistical and Perceptual Audio Processing. 2004.

[15] Non-negative matrix factorization based compensation of music for automatic speech recognition, Bhiksha Raj, T. Virtanen, Sourish Chaudhure, Rita Singh, 2010.

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