A text-dependent speaker-recognition system
Document type :
Communication dans un congrès avec actes
Title :
A text-dependent speaker-recognition system
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]
Matériaux et Acoustiques pour MIcro et NAno systèmes intégrés - IEMN [MAMINA - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Debavelaere-Callens, Dorothée [Auteur]
Matériaux et Acoustiques pour MIcro et NAno systèmes intégrés - IEMN [MAMINA - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
University of Balamand [Liban] [UOB]
Abche, Antoine [Auteur]
University of Balamand [Liban] [UOB]
Karam, Elie [Auteur]
University of Balamand [Liban] [UOB]
Nassar, Georges [Auteur]

Matériaux et Acoustiques pour MIcro et NAno systèmes intégrés - IEMN [MAMINA - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Debavelaere-Callens, Dorothée [Auteur]
Matériaux et Acoustiques pour MIcro et NAno systèmes intégrés - IEMN [MAMINA - IEMN]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Conference title :
IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
City :
Torino
Country :
Italie
Start date of the conference :
2017-05-22
Book title :
IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Journal title :
Proceedings of 2017 IEEE International Instrumentation and Measurement Technology Conference, IEEE I2MTC 2017
Publisher :
IEEE
Publication date :
2017
English keyword(s) :
Voice recognition
speaker identification
STFT
collar
piezoelectric transducer
speaker identification
STFT
collar
piezoelectric transducer
HAL domain(s) :
Sciences de l'ingénieur [physics]
Physique [physics]
Physique [physics]
English abstract : [en]
In this work, a voice recognition approach is developed and presented. It is a based on acquiring the signal of vocal cords' vibrations of a person using a piezoelectric transducer element attached on a collar wrapped ...
Show more >In this work, a voice recognition approach is developed and presented. It is a based on acquiring the signal of vocal cords' vibrations of a person using a piezoelectric transducer element attached on a collar wrapped around the neck. The recognition is then based on the vocal cords vibrations' pressure of the individuals and not their normal voices. Due to the varying nature of the collected signal, the analysis was performed by applying the Short Term Fourier Transform technique to decompose the signal into its frequency components. These frequencies represent the vocal folds vibrations' frequencies (100-1000 Hz). The features in terms of frequencies' interval are extracted from the resulting spectrogram. Then, 1-D vector is formed for identification purposes. The person's identification is performed using the correlation coefficient as a similarity measure. The results show that a high percentage of recognition is achieved and the performance is much better than many existing techniques in the literature.Show less >
Show more >In this work, a voice recognition approach is developed and presented. It is a based on acquiring the signal of vocal cords' vibrations of a person using a piezoelectric transducer element attached on a collar wrapped around the neck. The recognition is then based on the vocal cords vibrations' pressure of the individuals and not their normal voices. Due to the varying nature of the collected signal, the analysis was performed by applying the Short Term Fourier Transform technique to decompose the signal into its frequency components. These frequencies represent the vocal folds vibrations' frequencies (100-1000 Hz). The features in terms of frequencies' interval are extracted from the resulting spectrogram. Then, 1-D vector is formed for identification purposes. The person's identification is performed using the correlation coefficient as a similarity measure. The results show that a high percentage of recognition is achieved and the performance is much better than many existing techniques in the literature.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :