An effective age detection method based on short time energy and zero crossing rate

The aim of this paper is to find the distinction of different age group of people by calculating short time energy (STE) and zero crossing rate (ZCR) of voiced segments of a speech signal. The STE and ZCR are two widely accepted method for the purpose of distinguishing voiced and unvoiced part of a speech signal. The physiological properties of human organs such as the glottis and the vocal tract are subject to change due to age and gender differences. Since these physical changes are reflected in the speech signal, so acoustics measures related to these properties may be helpful for speaker age detection. In the present study speech samples are recorded from six speakers including three males and three females (i.e. age 50, 30 and 10). Experimental results show that the age 50 male and female informants corresponding to STE and ZCR plots depicting clarity of the speaker's identification with lower age group.