LR Parsing with a Category Reachability Test Applied to Speech Recognition

Kenji KITA  Tsuyoshi MORIMOTO  Shigeki SAGAYAMA  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E76-D   No.1   pp.23-28
Publication Date: 1993/01/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Speech and Discourse Processing in Dialogue Systems)
Category: 
Keyword: 
speech recognition,  HMMs,  LR parsing,  reachability,  LR-CRT algorithm,  

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Summary: 
In this paper, we propose an extended LR parsing algorithm, called LR parsing with a category reachability test (the LR-CRT algorithm). The LR-CRT algorithm enables a parser to efficiently recognize those sentences that belong to a specified grammatical category. The key point of the algorithm is to use an augmented LR parsing table in which each action entry contains a set of reachable categories. When executing a shift or reduce action, the parser checks whether the action can reach a given category using the augmented table. We apply the LR-CRT algorithm to improve a speech recognition system based on two-level LR parsing. This system uses two kinds of grammars, inter- and intra-phrase grammars, to recognize Japanese sentential speech. Two-level LR parsing guides the search of speech recognition through two-level symbol prediction, phrase category prediction and phone prediction, based on these grammars. The LR-CRT algorithm makes possible the efficient phone prediction based on the phrase category prediction. The system was evaluated using sentential speech data uttered phrase by phrase, and attained a word accuracy of 97.5% and a sentence accuracy of 91.2%