| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Thesis and Dissertation
|
Research Section | Available | MP/16-55 |
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%.
There are no comments on this title.
Text