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Adaptive harmonic time-frequency decomposition of audio using shift-invariant PLCA

  • CNRS LTCI

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Résumé

Numerous methods have been developed for the time-frequency analysis and smart decomposition of audio signals. However, these techniques are not consistently suitable for real music signals where each note presents continuous variations of both pitch and spectral envelope. This paper presents a new model for analyzing the harmonic structures of an audio signal that can jointly handle those two types of variations. Each note in a constant-Q transform is modeled as a weighted sum of narrowband parametric spectra, and positive deconvolution is performed to estimate the model parameters, in the framework of probabilistic latent component analysis. The algorithm has been tested in a task of monopitch estimation. The very promising results highlight the reliability and the robustness of the model.

langue originaleAnglais
titre2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
Pages401-404
Nombre de pages4
Les DOIs
étatPublié - 18 août 2011
Modification externeOui
Evénement36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Prague, République tchcque
Durée: 22 mai 201127 mai 2011

Série de publications

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

Une conférence

Une conférence36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Pays/TerritoireRépublique tchcque
La villePrague
période22/05/1127/05/11

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