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        <title>Probabilistic LR Parsing for Speech Recognition</title>
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            <title>Proceedings of the First International Workshop on Parsing Technologies</title>
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            <namePart type="given">Masaru</namePart>
            <namePart type="family">Tomita</namePart>
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            <publisher>Carnegy Mellon University</publisher>
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    <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.</abstract>
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%0 Conference Proceedings
%T Probabilistic LR Parsing for Speech Recognition
%A Wright, J. H.
%A Wrigley, E. N.
%Y Tomita, Masaru
%S Proceedings of the First International Workshop on Parsing Technologies
%D 1989
%8 August
%I Carnegy Mellon University
%C Pittsburgh, Pennsylvania, USA
%F wright-wrigley-1989-probabilistic
%X 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.
%U https://aclanthology.org/W89-0211
%P 105-114

Markdown (Informal)

[Probabilistic LR Parsing for Speech Recognition](https://aclanthology.org/W89-0211) (Wright & Wrigley, IWPT 1989)

• Probabilistic LR Parsing for Speech Recognition (Wright & Wrigley, IWPT 1989)

ACL

• J. H. Wright and E. N. Wrigley. 1989. Probabilistic LR Parsing for Speech Recognition. In Proceedings of the First International Workshop on Parsing Technologies, pages 105–114, Pittsburgh, Pennsylvania, USA. Carnegy Mellon University.