Yoh'ichi Tohkura
A Weighted Cepstral Distance Measure
for Speech Recognition
Abstract:A weighted cepstral distance measure is proposed and is tested in a speaker-independent
isolated word recognition system using standard DTW (Dynamic Time Warping) techniques.
The measure is a statistically weighted distance measure with weights equal to the inverse
variance of the cepstral coefficients. The experimental results show that the weighted cepstral
distance measure works substantially better than both the Euclidean cepstral distance and the
log likelihood ratio distance measures across two different data bases. The recognition error rate obtained using the weighted cepstral distance measure was about 1% for digit recognition.
This result was less than one fourth of that obtained using the simple Euclidean cepstral
distance measure and about one third of the results using the log likelihood ratio distance
measure. The most significant performance characteristic of the weighted cepstral distance
was that it tended to equalize the performance of the recognizer across different talkers.