Title :
Singer melody extraction in polyphonic signals using source separation methods
Author :
Durrieu, Jean-Louis ; Richard, Gaël ; David, Bertrand
Author_Institution :
CNRS LTCI, TELECOM ParisTech, Paris
fDate :
March 31 2008-April 4 2008
Abstract :
We propose a new approach for singer melody extraction, based on blind source separation techniques. The short time Fourier transform (STFT) of the singer signal is modelled by a Gaussian mixture model (GMM) explicitly coupled with a generative source/filter model. We then introduce a simplification of this general GMM and approximate the STFT of the music signal using Non-negative Matrix Factorization (NMF) techniques. The melody line is extracted from the explicit source component of the model thanks to a Viterbi algorithm. The results are very promising and comparable or better than those of state-of-the-art systems.
Keywords :
Fourier transforms; Gaussian processes; approximation theory; audio signal processing; blind source separation; feature extraction; matrix decomposition; maximum likelihood estimation; music; Gaussian mixture model; Viterbi algorithm; approximation theory; blind source separation; generative source-filter model; music signal; nonnegative matrix factorization; polyphonic audio recording; short time Fourier transform; singer melody extraction; Blind source separation; Contracts; Covariance matrix; Databases; Fourier transforms; Humans; Multiple signal classification; Music; Source separation; Wiener filter; Blind Source Separation; Music; Non-Negative Matrix Factorization; Source/Filter Model; Spectral Analysis;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2008. ICASSP 2008. IEEE International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4244-1483-3
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2008.4517573