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COMPARISON OF NEURAL NETWORKS FOR SPEAKER RECOGNITION
 

Summary: COMPARISON OF NEURAL NETWORKS FOR SPEAKER
RECOGNITION
Rita H Wouhaybi Mohamad Adnan Al-Alaoui1
IEEE Member IEEE Senior Member
IncoNet sal American University of Beirut
PO Box 113-6678 Hamra Street 850 Third Avenus, 18th
Floor
Beirut Lebanon New York, NY 10022 USA
email: r.h.wouhaybi@ieee.org email: adnan@aub.edu.lb
Abstract
In a world where authentication and privacy are
taking a lot of our daily efforts, it is becoming
more important for us to prove our identity to
different systems every day so that we can access
required and useful services.
The problem addressed in this research is speaker
verification as it involves knowing the identity of a
given speaker using a predefined set of samples.
The steps of this process start with processing the
voice signal using the Fast Fourier Transform

  

Source: Al-Alaoui, Mohamad Adnan - Faculty of Engineering and Architecture, American University of Beirut, Lebanon

 

Collections: Engineering