A context-free grammar-driven, one-pass HMM-based continuous speech recognition method

Abstract

This paper describes a frame synchronous continuous speech recognition algorithm using a context-free grammar and its evaluation. A frame-synchronous parsing algorithm for context-free grammar based on the top-down strategy is used for the prediction of successive words. The parsing process is incorporated into the one-pass search algorithm with the dynamical expansion of a finite-state automaton. Of course, since the number of the states becomes large, the beam search method should be used in the prediction and in pruning unreliable candidate branches from the search space. By using the proposed algorithm, a sentence recognition rate of 90 percent in a speaker adaptation mode is obtained while the conventional system based on word spotting and lattice parsing algorithm obtained 80.7 percent for the task of perplexity 10.