Language Modeling Using Patterns Extracted from Parse Trees for Speech Recognition

Takatoshi JITSUHIRO  Hirofumi YAMAMOTO  Setsuo YAMADA  Genichiro KIKUI  Yoshinori SAGISAKA  

IEICE TRANSACTIONS on Information and Systems   Vol.E86-D   No.3   pp.446-453
Publication Date: 2003/03/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Issue on Speech Information Processing)
Category: Speech and Speaker Recognition
speech recognition,  language model,  n-gram model,  parser,  pattern model,  

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We propose new language models to represent phrasal structures by patterns extracted from parse trees. First, modified word trigram models are proposed. They are extracted from sentences analyzed by the preprocessing of the parser with knowledge. Since sentences are analyzed to create sub-trees of a few words, these trigram models can represent relations among a few neighbor words more strongly than conventional word trigram models. Second, word pattern models are used on these modified word trigram models. The word patterns are extracted from parse trees and can represent phrasal structures and much longer word-dependency than trigram models. Experimental results show that modified trigram models are more effective than traditional trigram models and that pattern models attain slight improvements over modified trigram models. Furthermore, additional experiments show that pattern models are more effective for long sentences.