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    <subfield code="a">12MS(IT)06</subfield>
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    <subfield code="a">Ali Muhammad Aamur</subfield>
    <subfield code="a">12MSIT06</subfield>
    <subfield code="a">Supervisor Prof. Dr. Akhtar Hussain Jalbani</subfield>
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    <subfield code="a">Gender Classification Through Voice Recognition</subfield>
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    <subfield code="a">Nawabshah</subfield>
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    <subfield code="a">ABSTRACT

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%.
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    <subfield code="a">Department of Information Technology</subfield>
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    <subfield code="u">https://tinyurl.com/5622j83v</subfield>
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    <subfield code="c">THESIS</subfield>
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    <subfield code="a">RESEARCH</subfield>
    <subfield code="b">RESEARCH</subfield>
    <subfield code="d">2018-03-27</subfield>
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    <subfield code="p">MP/16-55</subfield>
    <subfield code="r">2018-03-27 00:00:00</subfield>
    <subfield code="y">THESIS</subfield>
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