Isolated word recognition based on finite-state vector quantization

TLDR: An isolated word recognition system based on the finite-state vector quantization (FSVQ) method is proposed that requires far less search time, and needs no segmentation of input speech, yet yields comparable recognition accuracies.

Abstract: In this paper, we propose an isolated word recognition system based on the finite-state vector quantization (FSVQ) method. The recognition system can be viewed as a finite state machine composed of a codebook and next-state functions. As compared to an isolated word recognition system that uses the conventional memoryless vector quantization, the proposed system requires far less search time, and needs no segmentation of input speech, yet yields comparable recognition accuracies. For the design of next-state functions, two techniques, that is, the conditional histogram and omniscient design methods, are used, and their performances are compared in recognition of the ten Korean digits.