Word Recognition Acceleration by Double Random Seed Matching in Perceptual Cepstrum Error Space

Abstract

Paper presents an algorithm for acceleration of the dynamic time warping (DTW) based isolated word recognition algorithm. The number of matching operations directly depends on the size of vocabulary. A set of perceptual cepstrum features is calculated for each word and stored in the vocabulary as a reference. Additionally all words (references) are compared between each other using DTW in order to get the reference-to-reference matches. The acceleration of pattern matching is acquired by adaptive search of the pattern reference according to the previous matching results and reference-to-reference matches. A modified word selection scenario applied for the vocabulary reduces the number of matching operations by 62-70 % in average. The reduction of matching operations allows to use DTW based speech recognition methods in real-time control applications and only need additional 13 % of vocabulary storage space.