acl acl2010 acl2010-59 acl2010-59-reference knowledge-graph by maker-knowledge-mining
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Author: Frank Keller
Abstract: We pose the development of cognitively plausible models of human language processing as a challenge for computational linguistics. Existing models can only deal with isolated phenomena (e.g., garden paths) on small, specifically selected data sets. The challenge is to build models that integrate multiple aspects of human language processing at the syntactic, semantic, and discourse level. Like human language processing, these models should be incremental, predictive, broad coverage, and robust to noise. This challenge can only be met if standardized data sets and evaluation measures are developed.
Altmann, Gerry T. M. and Mark J. Steedman. 1988. Interaction with context during human sentence processing. Cognition 30(3): 191–238. Baayen, R. H., D. J. Davidson, and D. M. Bates. 2008. Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language to appear. Bachrach, Asaf. 2008. Imaging Neural Correlates of Syntactic Complexity in a Naturalistic Context. Ph.D. thesis, Massachusetts Institute of Technology, Cambridge, MA. Brants, Thorsten and Matthew W. Crocker. 2000. Probabilistic parsing and psychological plausibility. In Proceedings of the 18th Interna- tional Conference on Computational Linguistics. Saarbr¨ ucken/Luxembourg/Nancy, pages 111–1 17. Crocker, Matthew W. and Thorsten Brants. 2000. Wide-coverage probabilistic sentence processing. Journal of Psycholinguistic Research 29(6):647–669. Demberg, Vera and Frank Keller. 2008a. Data from eye-tracking corpora as evidence for theories of syntactic processing complexity. Cognition 101(2): 193–210. Demberg, Vera and Frank Keller. 2008b. A psycholinguistically motivated version of TAG. In Proceedings of the 9th International Workshop on Tree Adjoining Grammars and Related Formalisms. T ¨ubingen, pages 25–32. Demberg, Vera and Frank Keller. 2009. A computational model of prediction in human parsing: Unifying locality and surprisal effects. In Niels Taatgen and Hedderik van Rijn, editors, Proceedings of the 31st Annual Conference of the Cognitive Science Society. Cognitive Science Society, Amsterdam, pages 1888–1893. Dubey, Amit. 2010. The influence of discourse on syntax: A psycholinguistic model of sentence processing. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Uppsala. Dubey, Amit, Frank Keller, and Patrick Sturt. 2008. A probabilistic corpus-based model of syntactic parallelism. Cognition 109(3):326– 344. Ferrara Boston, Marisa, John Hale, Reinhold Kliegl, Umesh Patil, and Shravan Vasishth. 2008. Parsing costs as predictors of reading difficulty: An evaluation using the Potsdam Sentence Corpus. Journal of Eye Movement Research 2(1): 1–12. Ferreira, Fernanda, Kiel Christianson, and Andrew Hollingworth. 2001. Misinterpretations of garden-path sentences: Implications for models of sentence processing and reanalysis. Journal of Psycholinguistic Research 30(1):3–20. Frank, Stefan L. 2009. Surprisal-based comparison between a symbolic and a connectionist model of sentence processing. In Niels Taat- gen and Hedderik van Rijn, editors, Proceedings of the 31st Annual Conference of the Cognitive Science Society. Cognitive Science Society, Amsterdam, pages 1139–1 144. Garnsey, Susan M., Neal J. Pearlmutter, Elisabeth M. Myers, and Melanie A. Lotocky. 1997. The contributions of verb bias and plausibility to the comprehension of temporarily ambiguous sentences. Journal of Memory and Language 37(1):58–93. Gibson, Edward. 1998. Linguistic complexity: locality of syntactic dependencies. Cognition 68: 1–76. Grodner, Dan and Edward Gibson. 2005. Consequences of the serial nature of linguistic input. Cognitive Science 29:261–291 . Haji cˇ, Jan, editor. 2009. Proceedings of the 13th Conference on Computational Natural Language Learning: Shared Task. Association for Computational Linguistics, Boulder, CO. Hale, John. 2001. A probabilistic Earley parser as a psycholinguistic model. In Proceedings of the 2nd Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, Pittsburgh, PA, volume 2, pages 159–166. Hart, Betty and Todd R. Risley. 1995. Meaningful Differences in the Everyday Experience of Young American Children. Paul H. Brookes, Baltimore, MD. Jurafsky, Daniel. 1996. A probabilistic model of lexical and syntactic access and disambiguation. Cognitive Science 20(2): 137–194. Kamide, Yuki, Gerry T. M. Altmann, and Sarah L. Haywood. 2003. The time-course of prediction in incremental sentence processing: Evidence 65 from anticipatory eye movements. Journal of Memory and Language 49: 133–156. Kehler, Andrew, Laura Kertz, Hannah Rohde, and Jeffrey L. Elman. 2008. Coherence and coreference revisited. Journal of Semantics 25(1): 1– 44. Kennedy, Alan and Joel Pynte. 2005. Parafovealon-foveal effects in normal reading. Vision Research 45: 153–168. Klein, Dan and Christopher Manning. 2002. A generative constituent-context model for improved grammar induction. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics. Philadelphia, pages 128–135. Kliegl, Reinhold, Antje Nuthmann, and Ralf Engbert. 2006. Tracking the mind during reading: The influence of past, present, and future words on fixation durations. Journal of Experimental Psychology: General 135(1): 12–35. Landauer, Thomas K. and Susan T. Dumais. 1997. A solution to Plato’s problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychological Review 104(2):21 1–240. Levy, Roger. 2008. Expectation-based syntactic comprehension. Cognition 106(3): 1126–1 177. McRae, Ken, Michael J. Spivey-Knowlton, and Michael K. Tanenhaus. 1998. Modeling the influence of thematic fit (and other constraints) in on-line sentence comprehension. Journal of Memory and Language 38(3):283–3 12. Mitchell, Jeff, Mirella Lapata, Vera Demberg, and Frank Keller. 2010. Syntactic and semantic factors in processing difficulty: An integrated measure. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Uppsala. Mitchell, Tom M., Svetlana V. Shinkareva, Andrew Carlson, Kai-Min Chang, Vicente L. Malave, Robert A. Mason, and Marcel Adam Just3. 2008. Predicting human brain activity associated with the meanings of nouns. Science 320(5880): 1191–1 195. Murphy, Brian, Marco Baroni, and Massimo Poesio. 2009. EEG responds to conceptual stimuli and corpus semantics. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Singapore, pages 619– 627. Narayanan, Srini and Daniel Jurafsky. 2002. A Bayesian model predicts human parse preference and reading time in sentence processing. In Thomas G. Dietterich, Sue Becker, and Zoubin Ghahramani, editors, Advances in Neural Information Processing Systems 14. MIT Press, Cambridge, MA, pages 59–65. Pad o´, Ulrike, Matthew W. Crocker, and Frank Keller. 2009. A probabilistic model of semantic plausibility in sentence processing. Cognitive Science 33(5):794–838. Patil, Umesh, Shravan Vasishth, and Reinhold Kliegl. 2009. Compound effect of probabilistic disambiguation and memory retrievals on sentence processing: Evidence from an eyetracking corpus. In A. Howes, D. Peebles, and R. Cooper, editors, Proceedings of 9th International Conference on Cognitive Modeling. Manchester. Pickering, Martin J. and Martin J. Traxler. 1998. Plausibility and recovery from garden paths: An eye-tracking study. Journal of Experimental Psychology: Learning Memory and Cognition 24(4):940–961. Pickering, Martin J., Matthew J. Traxler, and Matthew W. Crocker. 2000. Ambiguity resolution in sentence processing: Evidence against frequency-based accounts. Journal of Memory and Language 43(3):447–475. Pynte, Joel, Boris New, and Alan Kennedy. 2008. On-line contextual influences during reading normal text: A multiple-regression analysis. Vision Research 48(21):2172–2183. Roark, Brian, Asaf Bachrach, Carlos Cardenas, and Christophe Pallier. 2009. Deriving lexical and syntactic expectation-based measures for psycholinguistic modeling via incremental top-down parsing. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Singapore, pages 324–333. Roland, Douglas and Daniel Jurafsky. 2002. Verb sense and verb subcategorization probabilities. In Paola Merlo and Suzanne Stevenson, editors, The Lexical Basis of Sentence Processing: Formal, Computational, and Experimental Issues, John Bejamins, Amsterdam, pages 325–346. Sanford, Anthony J. and Patrick Sturt. 2002. 66 Depth of processing in language comprehen- sion: Not noticing the evidence. Trends in Cognitive Sciences 6:382–386. Schuler, William, Miller, coverage and Lane parsing Samir AbdelRahman, Schwartz. using 2010. human-like Tim Broadmem- ory constraints. Computational Linguistics 26(1): 1–30. Staub, Adrian and Charles Clifton. 2006. Syntactic prediction in language comprehension: Evidence from either . . . or. Journal of Experimental Psychology: Learning, Memory, and Cognition 32:425–436. Stewart, Andrew J., Martin J. Pickering, and Anthony J. Sanford. 2000. The time course of the influence of implicit causality information: Focusing versus integration accounts. Journal of Memory and Language 42(3):423–443. Sturt, Patrick and Vincenzo Lombardo. 2005. Processing coordinated structures: Incrementality and connectedness. Cognitive Science 29(2):291–305. Tanenhaus, Michael K., Michael J. SpiveyKnowlton, Kathleen M. Eberhard, and Julie C. Sedivy. 1995. Integration of visual and linguistic information in spoken language comprehension. Science 268: 1632–1634. Vasishth, Shravan and Richard L. Lewis. 2006. Argument-head distance and processing complexity: Explaining both locality and antilocality effects. Language 82(4):767–794. 67