DocumentCode
699157
Title
Glottal opening instant detection from speech signal
Author
Bouzid, Aicha ; Ellouze, Noureddine
Author_Institution
Nat. Sch. of Eng. of Tunis, Tunis, Tunisia
fYear
2004
fDate
6-10 Sept. 2004
Firstpage
729
Lastpage
732
Abstract
Nowadays, new techniques of speech processing such as speech recognition and speech synthesis use the glottal closure and opening instants. Recognition techniques use them for the vocal folds description and for the classification of speaker´s state or for speaker classification, and speech synthesis techniques use them for the speech timbre.Nowadays, new techniques of speech processing such as speech recognition and speech synthesis use the glottal closure and opening instants. Recognition techniques use them for the vocal folds description and for the classification of speaker´s state or for speaker classification, and speech synthesis techniques use them for the speech timbre. In an effort to develop techniques that enhance data-driven techniques in speaker characterisation for speech synthesis, this paper describes a new method for automatically determining the location of the closed phase delimited by the glottal closure and opening instants. The proposed approach for detecting the glottal opening is based on multi scale products of wavelet transform of speech signal at different scales with enhancement of edge detection and estimation. It is shown that the method is effective and robust for speech singularity detection such as glottal opening instant as product is a processing which reinforces edge detection.
Keywords
edge detection; signal classification; speaker recognition; speech enhancement; speech synthesis; wavelet transforms; data-driven technique; edge detection enhancement; glottal opening instant detection; speaker characterisation; speaker classification; speech processing; speech recognition technique; speech singularity detection; speech synthesis techniques; speech timbre; vocal fold description; wavelet transform; Abstracts; Bridges; Image edge detection; Maximum likelihood detection; Nonlinear filters; Robustness; Speech;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2004 12th European
Conference_Location
Vienna
Print_ISBN
978-320-0001-65-7
Type
conf
Filename
7079687
Link To Document