The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 42-296
Full Name: Wael Al-Sawalmeh
Position: Assistant Professor
Age: ON
Sex: Male
Address: Philadelphia University , P.O. Box 1, Amman 19392,
Country: JORDAN
Tel: + 962-2-4799000
Tel prefix:
Fax: +962-2-4799037
E-mail address: narin912007@yahoo.com
Other E-mails: odaoud@philadelphia.edu.jo
Title of the Paper: SPEAKER IDENTIFICATION SYSTEM-BASED MEL FREQUENCY AND WAVELET TRANSFORM USING NEURAL NETWORK CLASSIFIER
Authors as they appear in the Paper: Wael Al-Sawalmeh,Khaled Daqrouq , Omar Daoud , Abdel-Rahman Al-Qawasmi
Email addresses of all the authors: narin912007@yahoo.com, haleddaq@yahoo.com, odaoud@philadelphia.edu.jo ,qawasmi@philadelphia.edu.jo
Number of paper pages: 10
Abstract: The robustness to noise in speaker identification systems is improved by applying Continuous Wavelet Transform (CWT). In this work, essential speaker features are used to investigate the identification accuracy in non-stationary signals. These features are extracted using Mel Frequency Cepstral Coefficients (MFCC) and CWT for speech signals. In order to classify extracted features, a Feed Forward Back Propagation Neural Network (FFBNN) is imposed, since it gives better classification accuracy over conventional methods. A simulation program used to test the performance of the proposed method at certain level of SNR (-6dB), showed a classification ratio equal to 99.7%.
Keywords: Speaker identification; Continuous wavelet transform; Cepstral coefficients; and Neural network.
EXTENSION of the file: .pdf
Special (Invited) Session:
Organizer of the Session:
How Did you learn about congress:
IP ADDRESS: 194.165.157.171