In this study, we do research in a proper microphone arrangement method by way of evaluating and analyzing the relation between an open angle of the microphones and a time difference of an input sound signal for an exact definition of a sound source. Then, We can expect that existing robots or machines with an only vision system will have more excellent environmental adaptation ability by supports of hearing sense.

This paper proposes a method to extract the personal information using a microphone array. Useful personal information, particularly customers, are age and gender. On the basis of these information, service applications for robots can satisfy users by offering services adaptive to the special needs of specific user groups that may include adults and children as well as females and males. We applied Gaussian Mixture Model (GMM) as a classifier and Mel Frequency Cepstral coefficients (MFCCs) as a voice feature. The major aim of this paper is to discover the voice source parameters of age and gender and to classify these two characteristics simultaneously. For the ubiquitous environment, voices obtained by the selected channels in a microphone array are useful to reduce background noise.