%0 Journal Article %1 noauthororeditor %A Ali, Md. Sadek %A Islam, Md. Shariful %A Hossain, Md. Alamgir %D 2012 %J International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) %K (FFT) Back-end Extraction Feature First Font-end Fourier Gender Recognition Transform %N 1 %P 01-09 %R 10.5121/ijcseit.2012.2101 %T GENDER RECOGNITION SYSTEM USING SPEECH SIGNAL %U http://airccse.org/journal/ijcseit/papers/2112ijcseit01.pdf %V 2 %X In this paper, a system, developed for speech encoding, analysis, synthesis and gender identification is presented. A typical gender recognition system can be divided into front-end system and back-end system. The task of the front-end system is to extract the gender related information from a speech signal and represents it by a set of vectors called feature. Features like power spectrum density, frequency at maximum power carry speaker information. The feature is extracted using First Fourier Transform (FFT) algorithm. The task of the back-end system (also called classifier) is to create a gender model to recognize the gender from his/her speech signal in recognition phase. This paper also presents the digital processing of a speech signals (pronounced “A” and “B”) which are taken from 10 persons, 5 of them are Male and the rest of them are Female. Power Spectrum Estimation of the signal is examined .The frequency at maximum power of the English Phonemes is extracted from the estimated power spectrum. The system uses threshold technique as identification tool. The recognition accuracy of this system is 80% on average.

@article{noauthororeditor, abstract = {In this paper, a system, developed for speech encoding, analysis, synthesis and gender identification is presented. A typical gender recognition system can be divided into front-end system and back-end system. The task of the front-end system is to extract the gender related information from a speech signal and represents it by a set of vectors called feature. Features like power spectrum density, frequency at maximum power carry speaker information. The feature is extracted using First Fourier Transform (FFT) algorithm. The task of the back-end system (also called classifier) is to create a gender model to recognize the gender from his/her speech signal in recognition phase. This paper also presents the digital processing of a speech signals (pronounced “A” and “B”) which are taken from 10 persons, 5 of them are Male and the rest of them are Female. Power Spectrum Estimation of the signal is examined .The frequency at maximum power of the English Phonemes is extracted from the estimated power spectrum. The system uses threshold technique as identification tool. The recognition accuracy of this system is 80% on average. }, added-at = {2018-08-06T11:01:15.000+0200}, author = {Ali, Md. Sadek and Islam, Md. Shariful and Hossain, Md. Alamgir}, biburl = {https://www.bibsonomy.org/bibtex/2aad51e8d6394f4716002637e80ef606c/ijcseit}, doi = {10.5121/ijcseit.2012.2101}, interhash = {16b261f77ef882c8dbf1959c57c75a7c}, intrahash = {aad51e8d6394f4716002637e80ef606c}, issn = {2231-3117 [Online] ; 2231-3605 [Print]}, journal = {International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)}, keywords = {(FFT) Back-end Extraction Feature First Font-end Fourier Gender Recognition Transform}, language = {English}, month = feb, number = 1, pages = {01-09}, timestamp = {2018-08-06T11:01:15.000+0200}, title = {GENDER RECOGNITION SYSTEM USING SPEECH SIGNAL }, url = {http://airccse.org/journal/ijcseit/papers/2112ijcseit01.pdf}, volume = 2, year = 2012 }