Discussed Spring 2011
Clark, A. & S. Lappin. (2011 forthcoming). Computational learning theory and language acquisition. In R. Kempson, N. Asher, and T. Fernando (eds.), Handbook of Philosophy of Linguistics. Elsevier.
Heinz, J. (2009). On the role of locality in learning stress patterns. Phonology, 26, 303–351.
Heinz, J (2010 forthcoming). Computational phonology part I: Foundations. To appear in Language and Linguistics Compass.
Heinz, J. (2010 forthcoming). Computational phonology part II: Grammars, learning, and the future. To appear in Language and Linguistics Compass.
Yu, K. (2010). Representational Maps from the Speech Signal to Phonological Categories: A Case Study with Lexical Tones. UCLA Working Papers in Linguistics, 15 (Papers in Mathematical Linguistics, 1), 1–30.
Reference Material to Readings
Clark, A. (2004). Grammatical inference and first language acquisition. In Workshop on Psycho-computational Models of Human Language Acquisition, Geneva, Switzerland.
Clark, A. & S. Lappin. (2009). Another look at indirect negative evidence. In Proceedings of the EACL Workshop on Cognitive Aspects of Computational Language Acquisition, Athens.
Gauthier, B., R. Shi, & Y. Xu. (2007). Learning phonetic categories by tracking movements. Cognition, 103, 80–106.
Heinz, J. (2006). Learning quantity insensitive stress systems via local inference. In Richard Wicentowski & Grzegorz Kondark (eds.), Proceedings of the 8th Meeting of the ACL Special Interest Group in Computational Phonology. New York City. 21–30.
Heinz, J. (2010 Ms). Computational theories of learning and developmental psycholinguistics, under review with The Cambridge Handbook of Developmental Linguistics.
Toscano, J., & B. McMurray. (2010). Cue integration with categories: Weighting acoustic cues in speech using unsupervised learning and distributional statistics. Cognitive Science 34, 434–464.
Vallabha, G., J. McClelland, F. Pons, J. Werker, & S. Amano. (2007). Unsupervised learning of vowel categories from infant-directed speech. Proceedings of the National Academy of Sciences, 104, 13273-13278.
Heinz, J. (2009). On the role of locality in learning stress patterns. Phonology, 26, 303–351.
Heinz, J (2010 forthcoming). Computational phonology part I: Foundations. To appear in Language and Linguistics Compass.
Heinz, J. (2010 forthcoming). Computational phonology part II: Grammars, learning, and the future. To appear in Language and Linguistics Compass.
Yu, K. (2010). Representational Maps from the Speech Signal to Phonological Categories: A Case Study with Lexical Tones. UCLA Working Papers in Linguistics, 15 (Papers in Mathematical Linguistics, 1), 1–30.
Reference Material to Readings
Clark, A. (2004). Grammatical inference and first language acquisition. In Workshop on Psycho-computational Models of Human Language Acquisition, Geneva, Switzerland.
Clark, A. & S. Lappin. (2009). Another look at indirect negative evidence. In Proceedings of the EACL Workshop on Cognitive Aspects of Computational Language Acquisition, Athens.
Gauthier, B., R. Shi, & Y. Xu. (2007). Learning phonetic categories by tracking movements. Cognition, 103, 80–106.
Heinz, J. (2006). Learning quantity insensitive stress systems via local inference. In Richard Wicentowski & Grzegorz Kondark (eds.), Proceedings of the 8th Meeting of the ACL Special Interest Group in Computational Phonology. New York City. 21–30.
Heinz, J. (2010 Ms). Computational theories of learning and developmental psycholinguistics, under review with The Cambridge Handbook of Developmental Linguistics.
Toscano, J., & B. McMurray. (2010). Cue integration with categories: Weighting acoustic cues in speech using unsupervised learning and distributional statistics. Cognitive Science 34, 434–464.
Vallabha, G., J. McClelland, F. Pons, J. Werker, & S. Amano. (2007). Unsupervised learning of vowel categories from infant-directed speech. Proceedings of the National Academy of Sciences, 104, 13273-13278.
Discussed Winter 2011
Bever, T. & Poeppel, D. (2010). Analysis by Synthesis: A (Re-)Emerging Program of Research for Language and Vision. Biolinguistics, 4:2-3, 174-200.
Chater, N. & Christiansen, M. (2010). Language Acquisition Meets Language Evolution. Cognitive Science, 34, 1131-1157.
Hruschka, D., Christiansen, M., Blythe, R., Croft, W., Heggarty, P., Mufwene, S., Pierrehumbert, J., & Poplack, S. (2009). Building social cognitive models of language change. Trends in Cognitive Sciences, 13:11, 464-469.
Lidz, J. (2010). Language Learning and Language Universals. Biolinguistics, 4:2-3, 201-217.
Lightfoot, D. (2010). Language acquisition and language change. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 677-684. doi: 10.1002/wcs.39.
Progovac, L. (2010). Syntax: Its Evolution and Its Representation in the Brain. Biolinguistics, 4.2-4.3, 234-254.
Reference Material to Readings
Hauser, M., Chomsky, N., & Fitch, T. (2002). The Faculty of Language: What Is It, Who Has It, and How Did It Evolve? Science, 298, 1569-1579.
Chater, N. & Christiansen, M. (2010). Language Acquisition Meets Language Evolution. Cognitive Science, 34, 1131-1157.
Hruschka, D., Christiansen, M., Blythe, R., Croft, W., Heggarty, P., Mufwene, S., Pierrehumbert, J., & Poplack, S. (2009). Building social cognitive models of language change. Trends in Cognitive Sciences, 13:11, 464-469.
Lidz, J. (2010). Language Learning and Language Universals. Biolinguistics, 4:2-3, 201-217.
Lightfoot, D. (2010). Language acquisition and language change. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 677-684. doi: 10.1002/wcs.39.
Progovac, L. (2010). Syntax: Its Evolution and Its Representation in the Brain. Biolinguistics, 4.2-4.3, 234-254.
Reference Material to Readings
Hauser, M., Chomsky, N., & Fitch, T. (2002). The Faculty of Language: What Is It, Who Has It, and How Did It Evolve? Science, 298, 1569-1579.
Discussed Summer 2010 & Fall 2010
Blanchard, D., Heinz, J., & Golinkoff, R. (2010). Modeling the contribution of phonotactic cues to the problem of word segmentation. Journal of Child Language, 27, 487-511.
Bod, R. (2009). From Exemplar to Grammar: A Probabilistic Analogy-Based Model of Language Learning. Cognitive Science, 33, 752-793.
Hsu, A. & Chater, N. (2010). The Logical Problem of Language Acquisition: A Probabilistic Perspective. Cognitive Science, 34, , 972-1016.
Johnson, M. & Goldwater, S. (2009). Improving nonparametric Bayesian inference: experiments on unsupervised word segmentation with adaptor grammars. Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the ACL, Boulder, Colorado, 317-325.
Jones, B., Johnson, M., & Frank, M. (2010). Learning Words and Their Meanings from Unsegmented Child-directed Speech. Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the ACL, Los Angeles, CA, 501-509.
Parisien, C. & Stevenson, S. (2010). Learning verb alternations in a usage-based Bayesian model. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Perfors, A., Tenenbaum, J., & Wonnacott, E. (2010). Variability, negative evidence, and the acquisition of verb argument constructions. Journal of Child Language, 37, 607-642.
Yang, C. (2010). Computational Models of Syntactic Acquisition. To appear in WIREs Cognitive Science.
Reference Material to Readings
Alishahi, A. & Stevenson, S. (2008). A Computational Model of Early Argument Structure Acquisition. Cognitive Science, 32, 789-834.
Fleck, M. (2008). Lexicalized phonotactic word segmentation. Proceedings of the Association for Computational Linguistics, 130-138.
Foraker, S., Regier, T., Kheterpal, N., Perfors, A., and Tenenbaum, J. (2009). Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One. Cognitive Science, 33, 287-300.
Frank, M., Goodman, N., & Tenenbaum, J. (2009). Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning. Psychological Science, 20(5), 578-585.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1), 21-54.
Kemp, C., Perfors, A., Tenenbaum, J. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Pearl, L., Goldwater, S., & Steyvers, M. (2010). How Ideal Are We? Incorporating Human Limitations into Bayesian Models of Word Segmentation. BUCLD 34: Proceedings of the 34th annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press, 315-326.
Perfors, A., Tenenbaum, J., & Regier, T. (2006). Poverty of the Stimulus? A Rational Approach. In R. Sun & N. Miyake (eds.) Proceedings of the 28th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society: 663-668.
Yang, C. (2004). Universal Grammar, statistics, or both? Trends in Cognitive Sciences, 8(10), 451-456.
Bod, R. (2009). From Exemplar to Grammar: A Probabilistic Analogy-Based Model of Language Learning. Cognitive Science, 33, 752-793.
Hsu, A. & Chater, N. (2010). The Logical Problem of Language Acquisition: A Probabilistic Perspective. Cognitive Science, 34, , 972-1016.
Johnson, M. & Goldwater, S. (2009). Improving nonparametric Bayesian inference: experiments on unsupervised word segmentation with adaptor grammars. Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the ACL, Boulder, Colorado, 317-325.
Jones, B., Johnson, M., & Frank, M. (2010). Learning Words and Their Meanings from Unsegmented Child-directed Speech. Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the ACL, Los Angeles, CA, 501-509.
Parisien, C. & Stevenson, S. (2010). Learning verb alternations in a usage-based Bayesian model. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Perfors, A., Tenenbaum, J., & Wonnacott, E. (2010). Variability, negative evidence, and the acquisition of verb argument constructions. Journal of Child Language, 37, 607-642.
Yang, C. (2010). Computational Models of Syntactic Acquisition. To appear in WIREs Cognitive Science.
Reference Material to Readings
Alishahi, A. & Stevenson, S. (2008). A Computational Model of Early Argument Structure Acquisition. Cognitive Science, 32, 789-834.
Fleck, M. (2008). Lexicalized phonotactic word segmentation. Proceedings of the Association for Computational Linguistics, 130-138.
Foraker, S., Regier, T., Kheterpal, N., Perfors, A., and Tenenbaum, J. (2009). Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One. Cognitive Science, 33, 287-300.
Frank, M., Goodman, N., & Tenenbaum, J. (2009). Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning. Psychological Science, 20(5), 578-585.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1), 21-54.
Kemp, C., Perfors, A., Tenenbaum, J. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Pearl, L., Goldwater, S., & Steyvers, M. (2010). How Ideal Are We? Incorporating Human Limitations into Bayesian Models of Word Segmentation. BUCLD 34: Proceedings of the 34th annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press, 315-326.
Perfors, A., Tenenbaum, J., & Regier, T. (2006). Poverty of the Stimulus? A Rational Approach. In R. Sun & N. Miyake (eds.) Proceedings of the 28th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society: 663-668.
Yang, C. (2004). Universal Grammar, statistics, or both? Trends in Cognitive Sciences, 8(10), 451-456.