Speaker identification using Dynamic Time Warping with stress compensation technique

In this paper, we present an algorithm for an isolated-word text-dependent speaker identification under normal and four stressful styles. The styles are : shout, slow, loud, and soft which are designed to simulate speech produced under real stressful conditions. The algorithm is based on Dynamic Time Warping (DTW) with cepstral stress compensation technique. Comparing DTW combined with cepstral stress compensation technique with DTW without cepstral stress compensation technique, the recognition rate has improved to some extent with a little increase in the computations. The recognition rate is improved : from 33 % to 67 % in shout style, from 51 % to 84 % in slow style, from 40 % to 80 % in loud style, and from 52 % to 70 % in soft style. Cepstral coefficients and transitional coefficients are combined to form an observation vector for Dynamic Time Warping. This algorithm is tested on a limited number of speakers due to our limited data base.