Stressful speech recognition method based on difference subspace integrated with dynamic time warping

Speech under G-Force was analyzed and considered as principal part and stressful part to research, which produced when speaker was under different acceleration of gravity. An isolated word recognition approach was proposed which integrated difference subspace means with dynamic time warping technique. The method recognized speech under G-Force by constructing a difference subspace to remove the stressful part. Dynamic time warping technique was adopted to make all feature vectors of one word in the training set have equal length, and a corresponding decision criterion was suggested. The experiments showed that for a small vocabulary including 15 words, the method obtained the average recognition rate of 98.3%, which almost equal to the rate in normal environment. The performance of general recognition system was degraded violently for the stressful speech, since G-Force had a direct physical impact on human speech production in addition to the influence on psychology. The method overcame the shortcoming perfectly, not only worked well in normal conditions but also had good performance for speech under G-Force.