GENDER RECOGNITION USING SPEECH PROCESSING TECHNIQUES IN LABVIEW
Kumar Rakesh, Subhangi Dutta, Kumara Shama · 2011
Traditionally the interest in voice-gender conversion was of a more theoretical nature rather than founded in real–life applications. However, with the increase in biometric security applications, mobile and automated telephonic communication and the resulting limitation in transmission bandwidth, practical applications of gender recognition have increased many folds. In this paper, using various speech processing techniques and algorithms, two models were made, one for generating Formant values of the voice sample and the other for generating pitch value of the voice sample. These two models were to be used for extracting gender biased features, i.e. Formant 1 and Pitch Value of a speaker. A preprocessing model was prepared in LabView for filtering out the noise components and also to enhance the high frequency formants in the voice sample. To calculate the mean of formants and pitch of all the samples of a speaker, a model containing loop and counters were implemented which generated a mean of Formant 1 and Pitch value of the speaker. Using nearest neighbor method, calculating Euclidean distance from the Mean value of Males and Females of the generated mean values of Formant 1 and Pitch, the speaker was classified between Male and Female. The algorithm was implemented in real time using NI LabVIEW.