000			01556nam a2200169Ia 4500
999			_c58159 _d58156
100			_a12MS(IT)06
100			_aAli Muhammad Aamur _a12MSIT06 _aSupervisor Prof. Dr. Akhtar Hussain Jalbani
245		0	_aGender Classification Through Voice Recognition
260			_aNawabshah
260			_bQUEST
260			_c2012
300			_a60
500			_aABSTRACT Artificial lntelligcnce is very progressive field of, which makes easy life of human, become dynamically innovations, and enhanced the area of computer technologies. ln area the speech recognition is huge and sensitive virtually complex. lt is able to classifying of human gender through voice recognition which is ambiguous of research, the strategies of this is to capture real time voice of human gender and extract the features by different methods. Although the fundamental frequency is, the major septum and fundamental frequency may contribute to the human discrimination of male and female voice categories. The Fast Fourier Transforms (FFT) plays the major aspect that convert the time domain to frequency domain. This analog toward digital transforming to decipher the and filter the noise and classify the gender either male or female. Naive Bayes classifier contribute for classification the independence assumption training where train the system with the help of male and female voice and classify after this. strategies the classification accuracy rate is 81%.
700			_aDepartment of Information Technology
856			_uhttps://tinyurl.com/5622j83v
942			_cTHESIS