An annotation scheme for free word order languages
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Probabilistic parsing and psychological plausibility
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
A probabilistic earley parser as a psycholinguistic model
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
A finite-state model of human sentence processing
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Incrementality in deterministic dependency parsing
IncrementParsing '04 Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
The influence of discourse on syntax a psycholinguistic model of sentence processing
ACL '10 Proceedings of the 48th Annual Meeting of the Association for 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
The role of memory in superiority violation gradience
CMCL '10 Proceedings of the 2010 Workshop on Cognitive Modeling and Computational Linguistics
Classification of atypical language in autism
CMCL '11 Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics
A model of discourse predictions in human sentence processing
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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An incremental dependency parser's probability model is entered as a predictor in a linear mixed-effects model of German readers' eye-fixation durations. This dependency-based predictor improves a baseline that takes into account word length, n-gram probability, and Cloze predictability that are typically applied in models of human reading. This improvement obtains even when the dependency parser explores a tiny fraction of its search space, as suggested by narrow-beam accounts of human sentence processing such as Garden Path theory.