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Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves. This technique makes it possible to use the speaker’s voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers.

This document demonstrates how a speaker recognition system can be designed by artificial neural network using Mel-Frequency Cepstrum Coefficients of voice signal. Note that the training process did not consist of a single call to a training function. Instead, the network was trained several times on various input ideal and noisy signals coded by Mel-Frequency Cepstrum Coefficients, the signals which contents voices. In this case training a network on different sets of noisy signals forced the network to learn how to deal with noise, a common problem in the real world.