A computational theory of human linguistic processing: memory limitations and processing breakdown
A computational theory of human linguistic processing: memory limitations and processing breakdown
The syntactic process
Probabilistic top-down parsing and language modeling
Computational Linguistics
Three generative, lexicalised models for statistical parsing
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Finite-state approximation of constraint-based grammars using left-corner grammar transforms
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A syntactic time-series model for parsing fluent and disfluent speech
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Toward a psycholinguistically-motivated model of language processing
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Lookahead in deterministic left-corner parsing
IncrementParsing '04 Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together
Word buffering models for improved speech repair parsing
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Broad-coverage parsing using human-like memory constraints
Computational Linguistics
Complexity metrics in an incremental right-corner parser
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
HHMM parsing with limited parallelism
CMCL '10 Proceedings of the 2010 Workshop on Cognitive Modeling and Computational Linguistics
Incremental combinatory categorial grammar and its derivations
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I
Incremental syntactic language models for phrase-based translation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Connectionist-inspired incremental PCFG parsing
CMCL '12 Proceedings of the 3rd Workshop on Cognitive Modeling and Computational Linguistics
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Statistical parsing models have recently been proposed that employ a bounded stack in time-series (left-to-right) recognition, using a right-corner transform defined over training trees to minimize stack use (Schuler et al., 2008). Corpus results have shown that a vast majority of naturally-occurring sentences can be parsed in this way using a very small stack bound of three to four elements. This suggests that the standard cubic-time CKY chart-parsing algorithm, which implicitly assumes an unbounded stack, may be wasting probability mass on trees whose complexity is beyond human recognition or generation capacity. This paper first describes a version of the right-corner transform that is defined over entire probabilistic grammars (cast as infinite sets of generable trees), in order to ensure a fair comparison between bounded-stack and unbounded PCFG parsing using a common underlying model; then it presents experimental results that show a bounded-stack right-corner parser using a transformed version of a grammar significantly outperforms an unbounded-stack CKY parser using the original grammar.