Singer melody extraction in polyphonic signals using source separation methods

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages169-172
Number of pages4
DOIs
Publication statusPublished - 16 Sept 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 20084 Apr 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period31/03/084/04/08

Keywords

  • Blind Source Separation
  • Music
  • Non-Negative Matrix Factorization
  • Source/Filter Model
  • Spectral Analysis

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