The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 29-293
Full Name: Abdel-Rahman Al-Qawasmi
Position: Assistant Professor
Age: ON
Sex: Male
Address: Philadelphia University -Amman 19392 P.O.Box 1
Country: JORDAN
Tel: 962777420872
Tel prefix: 962777420872
Fax:
E-mail address: qawasmi@philadelphia.edu.jo
Other E-mails: telecomjo@yahoo.com
Title of the Paper: The Use of Wavelets in Speaker Feature Tracking Identification System Using Neural Network
Authors as they appear in the Paper: Wael Al-Sawalmeh, Khaled Daqrouq, Abdel-Rahman Al-Qqawasmi, Tareq Abu-hilal
Email addresses of all the authors: narin912007@yahoo.com, haleddaq@yahoo.com,qawasmi@philadelphia.edu.jo, tr_helal@yahoo.com
Number of paper pages: 11
Abstract: Continuous and Discrete Wavelet Transform (WT) are used to create text-dependent robust to noise speaker recognition system. In this paper we investigate the accuracy of identification the speaker identity in non- stationary signals. Three methods are used to extract the essential speaker features based on Continuous, Discrete Wavelet Transform and Power Spectrum Density (PSD). To have better identification rate, two types of Neural Networks (NNT) are studied: The first is Feed Forward Back Propagation Neural Network (FFBNN) and the second is perceptron. Up to 98.44% identification rate is achieved. The presented system depends on the multi-stage features extracting due to its better accuracy. The multistage features tracking based system shows good capability of features tracking for tested signals with SNR equals to -9 dB using Wavelet Transform, which is suitable for non-stationary signal.
Keywords: Speaker identification; Continuous and discrete wavelet transform; Linear prediction coefficient; and text-dependent
EXTENSION of the file: .pdf
Special (Invited) Session: Multistage Speaker Feature Tracking Identification System Based on Continuous and Discrete Wavelet Transform
Organizer of the Session: 613-177
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IP ADDRESS: 194.165.157.171
