Title :

Speaker Identification Based On Vocal Cords Vibrations signal: Effect Of The Window

Author(s) :

Ishac, Dany [Auteur]
University of Balamand [Liban] [UOB]
Abche, Antoine [Auteur]
University of Balamand [Liban] [UOB]
Karam, Elie [Auteur]
University of Balamand [Liban] [UOB]
Nassar, Georges [Auteur]
INSA Institut National des Sciences Appliquées Hauts-de-France [INSA Hauts-De-France]
Matériaux et Acoustiques pour MIcro et NAno systèmes intégrés - IEMN [MAMINA - IEMN]
Debavelaere-Callens, Dorothée [Auteur]
INSA Institut National des Sciences Appliquées Hauts-de-France [INSA Hauts-De-France]
Matériaux et Acoustiques pour MIcro et NAno systèmes intégrés - IEMN [MAMINA - IEMN]

Journal title :

International journal of digital information and wireless communications (IJDIWC)

Pages :

58-62

Publisher :

Hong Kong : Society of Digital Information and Wireless Communications,

Publication date :

2018-03

ISSN :

2412-6551

English keyword(s) :

"Vocal cords vibration frequency"
"STFT"
"Barlett"
"Blackman"
"Hamming"
"Hanning"
"Rectangular"
"collar"
"transducer"
"speaker identification"

HAL domain(s) :

Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]/Acoustique [physics.class-ph]
Sciences de l'ingénieur [physics]/Matériaux
Sciences de l'ingénieur [physics]/Micro et nanotechnologies/Microélectronique

English abstract : [en]

A new speaker identification technique was proposed and presented. It is based on the acquisition of the individual’s signal of its vocal cords’ vibrations by attaching a piezoelectric transducer ...
Show more >A new speaker identification technique was proposed and presented. It is based on the acquisition of the individual’s signal of its vocal cords’ vibrations by attaching a piezoelectric transducer element to a collar and wrapping it around the neck. Having collected the signal, the Short Term Fourier Transform (STFT), in conjunction with a particular window, is applied on the signal to decompose it into its frequency components. Then, the resulting spectrogram is normalized, the noise is removed and the corresponding features are extracted for identification purposes. The performance of the developed approach in conjunction with various windows’ types (the Bartlett, the Blackman, the Hamming, the Hanning and the Rectangular windows) and window’s size is studied and evaluated quantitatively. The results show that the proposed approach using the Hamming window of size 64 yields the best accuracy in the identification of the desired individualsShow less >

Language :

Anglais

Popular science :

Non

Collections :

• Institut d'Électronique, de Microélectronique et de Nanotechnologie (IEMN) - UMR 8520

Source :

Harvested from HAL