Sixth European Conference on Speech Communication and Technology

We propose the utilization of a new npath binary tree search algorithm for vector quantization. Our target is to reduce the complexity (time processing) of the vector quantizer maintaining the quantization distortion. The algorithm has been applied to an isolated digit recognizer by telephone based on DHMM and to a speaker dependent continuous speech system based on SCHMM, so we will also give the recognition results for both of them. We have tested several alternatives to calculate the centroids of the higher levels of the tree. In all the experiments we have considered the following parameters for the evaluation: average distortion, same choice percentage, average distortion for the mistakes and processing time. Our reference has been the standard quantization (computing the distance with all centroids). In this reference case the distortion was 220.9 and the processing time was 2.1 seconds. With the npath binary tree search algorithm, we have obtained a 0.7 seconds processing time with a similar distortion: 226.4. In the semicontinuous system, we have obtained a reduction of 71 % in vector quantization processing time, maintaining the word accuracy.
Keywords: vector quantization, binary tree search, CPU time reduction
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Bibliographic reference. SanSegundo, R. / Córdoba, R. / Ferreiros, J. / Gallardo, A. / Colás, J. / Pastor, J. / López, Y. (1999): "Efficient vector quantization using an npath binary tree search algorithm", In EUROSPEECH'99, 9396.