Probabilistic LR Parsing for Speech Recognition

J. H. Wright, E. N. Wrigley


Abstract
An LR parser for probabilistic context-free grammars is described. Each of the standard versions of parser generator (SLR, canonical and LALR) may be applied. A graph-structured stack permits action conflicts and allows the parser to be used with uncertain input, typical of speech recognition applications. The sentence uncertainty is measured using entropy and is significantly lower for the grammar than for a first-order Markov model.
Anthology ID:
W89-0211
Volume:
Proceedings of the First International Workshop on Parsing Technologies
Month:
August
Year:
1989
Address:
Pittsburgh, Pennsylvania, USA
Venues:
IWPT | WS
SIG:
SIGPARSE
Publisher:
Carnegy Mellon University
Note:
Pages:
105–114
Language:
URL:
https://www.aclweb.org/anthology/W89-0211
DOI:
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/W89-0211.pdf