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A new Automatic Formant Tracking approach based on scalogram maxima detection using complex wavelets

Identifieur interne : 001191 ( Main/Exploration ); précédent : 001190; suivant : 001192

A new Automatic Formant Tracking approach based on scalogram maxima detection using complex wavelets

Auteurs : Imen Jemaa [Tunisie] ; Kais Ouni [Tunisie] ; Yves Laprie [France] ; Slim Ouni [France] ; Jean-Paul Haton [France]

Source :

RBID : Hal:hal-00836854

English descriptors

Abstract

In this paper we present a new formant tracking algorithm where the formant frequencies estimation was based on local maxima detection of a time frequency representation. This representation can be shown by a scalogram issued from a complex wavelet transform. The formant frequency candidates are validated as local maxima of scalogram which correspond to wavelet ridges. Then in the proposed algorithm, we have introduced the computation of center of gravity as tracking constraint. We tested our new algorithm by applying it on synthesized and natural voiced speech signals. The formant trajectories obtained by our algorithm were compared to those of manually-edited ones of our Arabic database as reference; those given by Fourier transform method and the LPC analysis used in Praat. The comparison of the results showed globally the adequacy of the first three formant trajectories using complex Morlet wavelet refers to the manually-edited formant tracks.

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Le document en format XML

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<term>arabic database</term>
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<div type="abstract" xml:lang="en">In this paper we present a new formant tracking algorithm where the formant frequencies estimation was based on local maxima detection of a time frequency representation. This representation can be shown by a scalogram issued from a complex wavelet transform. The formant frequency candidates are validated as local maxima of scalogram which correspond to wavelet ridges. Then in the proposed algorithm, we have introduced the computation of center of gravity as tracking constraint. We tested our new algorithm by applying it on synthesized and natural voiced speech signals. The formant trajectories obtained by our algorithm were compared to those of manually-edited ones of our Arabic database as reference; those given by Fourier transform method and the LPC analysis used in Praat. The comparison of the results showed globally the adequacy of the first three formant trajectories using complex Morlet wavelet refers to the manually-edited formant tracks.</div>
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