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Voice Source Parameters Estimation by Fitting the Glottal Formant and the Inverse Filtering Open Phase
Drugman, Thomas; Dubuisson, Thomas; Moinet, Alexis et al.
2008
 

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Abstract :
[en] This paper presents two approaches to the problem of extracting the parameters of the LF source model directly from the speech waveform. The first approach relies on the glottal formant estimated from the anticausal contribution of speech. Indeed the ZZT technique has recently shown its ability to deconvolve speech into its causal and anticausal components. The second method is based on the glottal open phase obtained by inverse filtering. The notion of unanalyzable frames and the way to detect and correct them are also presented. Once source parameters are extracted, the coefficients of the ARX speech production model are estimated by spectral division. Decomposition on both synthetic and natural speech, as well as an analysis-synthesis test confirm the accuracy of methods exposed.
Disciplines :
Electrical & electronics engineering
Library & information sciences
Author, co-author :
Drugman, Thomas ;  Université de Mons > Faculté Polytechnique > Information, Signal et Intelligence artificielle
Dubuisson, Thomas ;  Université de Mons > Faculté Polytechnique > Information, Signal et Intelligence artificielle
Moinet, Alexis ;  Université de Mons > Faculté Polytechnique > Information, Signal et Intelligence artificielle
D'alessandro, Nicolas
Dutoit, Thierry ;  Université de Mons > Faculté Polytechnique > Information, Signal et Intelligence artificielle
Language :
English
Title :
Voice Source Parameters Estimation by Fitting the Glottal Formant and the Inverse Filtering Open Phase
Publication date :
25 August 2008
Event name :
16th European Signal Processing Conference
Event place :
Lausanne, Switzerland
Event date :
2008
Research unit :
F105 - Information, Signal et Intelligence artificielle
Research institute :
R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique
R450 - Institut NUMEDIART pour les Technologies des Arts Numériques
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