Age and gender recognition from speech signals

Abstract

Abstract The aim of this research is to identify gender and age from speech, the system consists of two parts. The first part is called pre-processing and future extraction. The second part is called classification. This research investigates an automatic gender and age recognizer from speech. First four formant frequencies and twelve MFCCs are used to extract relevant features to recognize the gender. K-NN has been used as a classifier for the age recognizer model, stimulated using MATLAB. A special selectin of solid feature is used in this work to improve the accuracy of the gender and age classifiers based on the frequency range that the features represent.