GENDER IDENTIFICATION USING FUZZY LOGIC AND NEURAL NETWORK MODEL

Speech investigation is Art of the most exciting fields in Digital Signal Processing system. The reason only most of the researches have been made on it under the different resources tools and logical programs to generate an analysis that begin from speech production, speech recognition, speech processing, speech coding. F.J .Taylor is the initially to apply the analysis of speech signal [1]. In this research we handle the, males and females speech specimen of the utterance, 'Close', be used to make a system in Fuzzy Logic and then Neural Network to identify the male as of female words tone and similarity of between the results of the both systems, then the fuzzy logic approach was improving based on three features of the spokesman tone which are the signal value of the energy rate, the signal of the power spectrum and vowel sound ?letter O? in the word close. In this speech example to enlarge to ability in recognizing an individual speaker and then improve the system protection against intruders by building the system recognizes the vocalizations of a individual person register a voice approval authority of that person to make an access denied to unauthorized user to avoid accessing the system. The system shows good results during testing operation implement samples of one person next to others person like males and females samples.