We will refer to selections from the following books, in addition to the articles below:
Baker, M. (2008). The Macroparameter in a Microparametric World. In T. Biberauer (ed.), The Limits of Syntactic Variation, John Benjamins, Amsterdam, 351-374.
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.
Bonawitz, E., Denison, S., Chen, A., Gopnik, A., & Griffiths, T.L. (2011). A Simple Sequential Algorithm for Approximating Bayesian Inference. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin, TX: Cognitive Science Society.
Chemla, E., Mintz, T., Bernal, S., & Christophe, A. (2009). Categorizing Words Using "Frequent Frames": What Cross-Linguistic Analyses Reveal About Distributional Acquisition Strategies. Developmental Science.
Casserly, E. & Pisoni, D. (2010). Speech perception and production. Wiley Interdisciplinary Reviews: Cognitive Science, 1(5), 629-647
Clark, A. & Sakas, W. (2011). Computational Models of First Language Acquisition: Special Issue of Research on Language and Computation. Research on Language and Computation, 8(2).
Crain, C. & Pietroski, P. (2002). Why language acquisition is a snap. The Linguistic Review, 19, 163-183.
Denison, S., Reed, C., & Xu, F. (2011). The emergence of probabilistic reasoning in very young infants. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin, TX: Cognitive Science Society.
Dewar, K., & Xu, F. (2010). Induction, Overhypothesis, and the Origin of Abstract Knowledge: Evidence From 9-Month-Old Infants. Psychological Science, 21(12), , 1871-1877.
Dietrich, C., Swingley, D., & Werker, J.F. (2007). Native language governs interpretation of salient speech sound differences at 18 months. Proceedings of the National Academy of Sciences of the US, 16027-16031.
Dillon, B., Dunbar, E., & Idsardi, B. (2011 ms). A single stage approach to learning phonological categories: Insights from Inuktitut. University of Maryland, College Park and University of Massachusetts, Amherst.
Feldman, N., Griffiths, T., and Morgan, J. (2009). Learning phonetic categories by learning a lexicon. Proceedings of the 31st Annual Conference on Cognitive Science.
Feldman, N., Myers, E., White, K., Griffiths, T., & Morgan, J. (2011). Learners use word-level statistics in phonetic category acquisition. Proceedings of the 35th Boston University Conference on Language Development.
Finn, A. & Hudson Kam, C. (2008). The curse of knowledge: First language knowledge impairs adult learners’ use of novel statistics for word segmentation. Cognition, 108, 477-499.
Fleck, M. (2008). Lexicalized phonotactic word segmentation. In 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., Arnon, I., Tily, H., & Goldwater, S. (2010). Beyond Transitional Probabilities: Human Learners Impose a Parsimony Bias in Statistical Word Segmentation. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Frank, M., Goldwater, S., Griffiths, T., & Tenenbaum, J. (2010). Modeling human performance in statistical word segmentation. Cognition, 117(2), 107-125.
Frank, M., Goodman, N., & Tenenbaum, J. (2009). Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning. Psychological Science, 20(5), 578-585.
Freudenthal, D., Pine, J., & Gobet, F. (2010). Explaining quantitative variation in the rate of Optional Infinitive errors across languages: A comparison of MOSAIC and the Variational Learning Model. Journal of Child Language, 37(3), 643-669.
Gambell, T. & Yang, C. (2006). Word Segmentation: Quick but not dirty. Manuscript, Yale University.
Gerken, L. (2006). Decisions, decisions: infant language learning when multiple generalizations are possible. Cognition, 98, B67-B74.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2007). Distributional cues to word segmentation: Context is important. Proceedings of the 31st Boston University Conference on Language Development.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1), 21-54.
Gomez, R. & Gerken, L. (2000). Infant artificial language learning and language acquisition.Trends in Cognitive Sciences, 4(5), 178-186.
Goodluck, H. (2010). First language acquisition. Wiley Interdisciplinary Reviews: Cognitive Science, n/a. doi: 10.1002/wcs.95.
Hadley, P., Rispoli, M., Fitzgerald, C., & Bahnsen, A. (2011). Predictors of Morphosyntactic Growth in Typically Developing Toddlers: Contributions of Parent Input and Child Sex. Journal of Speech, Language, & Hearing Research, 54(2), 549-566.
Hewlett, D. & Cohen, P. (2009). Bootstrap voting experts. In Proceedings of the twenty-first international joint conference on artificial intelligence (IJCAI-09) 1071-1076.
Hsu, A. & Chater, N. (2010). The Logical Problem of Language Acquisition: A Probabilistic Perspective. Cognitive Science, 34, 972-1016.
Hudson Kam, C. & Newport, E.. (2009). Getting it right by getting it wrong: When learners change languages. Cognitive Psychology, 59, 30-66.
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.
Johnson, E. & Tyler, M. (2010). Testing the limits of statistical learning forwWord segmentation. Developmental Science, 13(2),339-345.
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.
Kam, X., Stoyneshka, I., Tornyova, L., Fodor, J., & Sakas, W. (2008). Bigrams and the Richness of the Stimulus. Cognitive Science, 32, 771-787.
Kemp, C., Perfors, A., Tenenbaum, J. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Kidd, C., Piantadosi, S., & Aslin, R. (2010). The Goldilocks Effect: Infants’ preference for stimuli that are neither too predictable nor too surprising. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Knight, K. Bayesian Inference with Tears. Manuscript downloaded from http://www.isi.edu/~knight/.
Lasnik, H. & Lohndal, T. (2010). Government–binding/principles and parameters theory. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 40–50. doi: 10.1002/wcs.35.
Legate, J. & Yang, C. (2002). Empirical re-assessment of stimulus poverty arguments. The Linguistic Review, 19, 151-162.
Legate, J. & Yang, C. (2007). Morphosyntactic learning and the development of tense. Language Acquisition, 14(3), 315-344.
Legate, J., & Yang, C. (2011). Assessing Child and Adult Grammar. To appear in R. Berwick & M., Piatelli-Palmarini (eds.), Rich Languages from Poor Inputs: In Honor of Carol Chomsky.
Lidz, J. (2010). Language Learning and Language Universals. Biolinguistics, 4(2-3), 201-217.
Lidz, J., Waxman, S., & Freedman, J. (2003). What infants know about syntax but couldn’t have learned: experimental evidence for syntactic structure at 18 months. Cognition, 89, B65-B73.
Liebbrandt, R. & Powers, D. (2010). Frequent Frames as Cues to Part-of-Speech in Dutch: Why Filler Frequency Matters. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Lightfoot, D. (2010). Language acquisition and language change. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 677–684. doi: 10.1002/wcs.39.
Marr, D. (1982). Vision. San Francisco: W.H. Freeman, pp. 3-43.
Maye, J., Werker, J., & Gerken, L. (2002). Infant sensitivity to distributional information can affect phonetic discrimination. Cognition, 82, , B101-B111.
McInnes, F., & Goldwater, S. (2011). Unsupervised extraction of recurring words from infant-directed speech Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin, TX.
Medina, T., Snedecker, J., Trueswell, J., & Gleitman, L. (2011). How words can and cannot be learned by observation Proceedings of the National Academy of Sciences, 1089014-9019.
Mintz, T. (2003). Frequent frames as a cue for grammatical categories in child directed speech.Cognition, 90, 91-117.
Mintz, T. (2006). Finding the verbs: distributional cues to categories available to young learners. In K. Hirsh-Pasek & R. M. Golinkoff (Eds.), Action Meets Word: How Children Learn Verbs (pp. 31-63). New York: Oxford University Press.
Mitchener, G. & Becker, M. (2011). Computational Models of Learning the Raising-Control Distinction. Research on Language and Computation, 8(2), 169-207.
Nevins, A. (2010). Two Case Studies in Phonological Universals: A View from Artificial Grammars. Biolinguistics, 4(2-3), 218-233.
Onnis, L., Monaghan, P., Richmond, K., & Chater, N. (2005). Phonology impacts segmentation in online speech processing. Journal of Memory and Language, 53, 225-237.
Pearl, L. (2008). Putting the Emphasis on Unambiguous: The Feasibility of Data Filtering for Learning English Metrical Phonology. In Chan, H., Jacob, H., and Kapia, E (eds.), BUCLD 32: Proceedings of the 32nd annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press, 390-401.
Pearl, L. (2009). Learning English Metrical Phonology: When Probability Distributions Are Not Enough. In Jean Crawford, Koichi Otaki, and Masahiko Takahashi (eds.), Proceedings of the 3rd Conference on Generative Approaches to Language Acquisition North America (GALANA 2008), Somerville, MA: Cascadilla Press, 200-211.
Pearl, L. (2010). Computational Models of Language Acquisition. In E. Blom & S. Unsworth (eds), Experimental Methods in Language Acquisition Research, John Benjamins.
Pearl, L. (2010 ms). When unbiased probabilistic learning is not enough: Acquiring a parametric system of metrical phonology. University of California, Irvine.
Pearl, L. & Goldwater, S. (2010 ms). Statistical Learning, Inductive Bias, and Bayesian Inference in Language Acquisition. University of California, Irvine and University of Edinburgh.
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.
Pearl, L., Goldwater, S., & Steyvers, M. (2011). Online Learning Mechanisms for Bayesian Models of Word Segmentation. Research on Language and Computation, 8(2), 107-132.
Pearl, L. & Lidz, J. (2009). When domain-general learning fails and when it succeeds: Identifying the contribution of domain-specificity. Language Learning & Development, 5(4), 235-265.
Pearl, L. & Lidz, J. (2010 ms.) Parameters in Language Acquisition. University of California, Irvine & University of Maryland, College Park.
Pearl, L., & Mis, B. (2011). How Far Can Indirect Evidence Take Us? Anaphoric One Revisited, In L. Carlson, C. Hölscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 879-884. Austin, TX: Cognitive Science Society.
Pearl, L., & Mis, B. (2011 submitted). What Indirect Evidence Can Tell Us About Universal Grammar: Anaphoric One Revisited. University of California, Irvine.
Pelham, S. (2011). The input ambiguity hypothesis and case blindness: an account of cross-linguistic and intra-linguistic differences in case errors. Journal of Child Language, 38, 235-272.
Perfors, A., Tenenbaum, J., Griffiths, T., & Xu, F., (2010 ms). A tutorial introduction to Bayesian models of cognitive development. University of Adelaide, Massachusetts Institute for Technology, and University of California, Berkeley.
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.
Perfors, A., Tenenbaum, J., & Regier, T. (2011). The learnability of abstract syntactic principles. Cognition, 118, 306-338.
Perfors, A., Tenenbaum, J., Griffiths, T., & Xu, F. (2011). A tutorial introduction to Bayesian models of cognitive development. Cognition, 120, 302-321.
Pinker, S. (2004). Clarifying the logical problem of language acquisition. Journal of Child Language, 31, 949-953.
Pullum, G. & Scholz, B. (2002). Empirical assessment of stimulus poverty arguments.The Linguistic Review, 19, 9-50.
Ramscar, M., Dye, M., Klein, J., Aguirre, N., Ruiz, L., & Saddat, L. (2011). Informativity versus logic: Children and adults take different approaches to word learning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Austin, TX.
Reali, F. & Christiansen, M. (2005). Structure Dependence in Language Acquisition: Uncovering the Richness of the Stimulus: Stucture Dependence and Indirect Statistical Evidence, Cognitive Science, 29, 1007-1028.
Regier, T., & Gahl, S. (2004). Learning the unlearnable: the role of missing evidence. Cognition, 93, 147-155.
Romberg, A. & Saffran, J. (2010). Statistical learning and language acquisition. Wiley Interdisciplinary Reviews: Cognitive Science, 1(6), 906-914.
Saffran, J.R., Aslin, R.N., & Newport, E.L. (1996). Statistical learning by 8-month old infants. Science, 274, 1926-1928.
Smith, L. & Yu, C. (2008). Infants rapidly learn word-referent mappings via cross-situational statistics. Cognition, 106, , 1558-1568.
Swingley, D. (2005). Statistical clustering and the contents of the infant vocabulary. Cognitive Psychology, 50, 86-132.
Swingley, D. (2009). Contributions of infant word learning to language development. Philosophical Transactions of the Royal Society B, 364, 3617-3632.
Syrett, K. & Lidz, J. (2010). 30-Month-Olds Use the Distribution and Meaning of Adverbs to Interpret Novel Adjectives,Language Learning and Development, 6(4), 258-282.
Vallabha, G., McClelland, J., Pons, F., Werker, J., & Amano, S. (2007). Unsupervised learning of vowel categories from infant-directed speech. Proceedings of the National Academy of Sciences of the U.S., 104(33), 13273-13278.
Wang, H. & Mintz, T. (2008). A Dynamic Learning Model for Categorizing Words Using Frames. In H. Chan, H. Jacob, & E. Kapia (eds.), BUCLD 32 Proceedings, 525-536.
Wang, H. & Mintz, T. (2010). From linear sequences to abstract structures: Distributional information in infant-direct speech. Paper presented at the 34th annual Boston University Conference on Language Development, Boston, MA.
Weisleder, A. & Waxman, S. (2010). What’s in the input? Frequent frames in child-directed speech offer distributional cues to grammatical categories in Spanish and English, Journal of Child Language, 37, 1089-1108.
Werker, J. (1995). Exploring Developmental Changes in Cross-language Speech Perception, Chapter 4 (pp.87-106) in Gleitman, L. & Liberman, M., Language. Cambridge, MA: The MIT Press.
Willits, J., Seidenberg, M., & Saffran, J. (2009). Verbs are LookING Good in Language Acquisition. Proceedings of the Annual Meeting of the Cognitive Science Society, VU University, Amsterdam, Netherlands.
Xu, F., & Tenenbaum, J. (2007). Word Learning as Bayesian Inference, Psychological Review, 114(2), 245-272.
Yang, C. (2004). Universal Grammar, statistics, or both? Trends in Cognitive Sciences, 8(10), 451-456.
Yang, C. (2010). Computational Models of Syntactic Acquisition. Revision to appear in Wiley Interdisciplinary Reviews: Cognitive Science.
Yoshida, K., Pons, F., Maye, J., & Werker, J. (2010). Distributional Phonetic Learning at 10 Months of Age Infancy, 15(4), 420-433.
Yu, C. & Smith, L. (2007). Rapid Word Learning Under Uncertainty via Cross-Situational Statistics. Psychological Science, 18(5), 414-420.
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.
Bonawitz, E., Denison, S., Chen, A., Gopnik, A., & Griffiths, T.L. (2011). A Simple Sequential Algorithm for Approximating Bayesian Inference. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin, TX: Cognitive Science Society.
Chemla, E., Mintz, T., Bernal, S., & Christophe, A. (2009). Categorizing Words Using "Frequent Frames": What Cross-Linguistic Analyses Reveal About Distributional Acquisition Strategies. Developmental Science.
Casserly, E. & Pisoni, D. (2010). Speech perception and production. Wiley Interdisciplinary Reviews: Cognitive Science, 1(5), 629-647
Clark, A. & Sakas, W. (2011). Computational Models of First Language Acquisition: Special Issue of Research on Language and Computation. Research on Language and Computation, 8(2).
Crain, C. & Pietroski, P. (2002). Why language acquisition is a snap. The Linguistic Review, 19, 163-183.
Denison, S., Reed, C., & Xu, F. (2011). The emergence of probabilistic reasoning in very young infants. In L. Carlson, C. Holscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin, TX: Cognitive Science Society.
Dewar, K., & Xu, F. (2010). Induction, Overhypothesis, and the Origin of Abstract Knowledge: Evidence From 9-Month-Old Infants. Psychological Science, 21(12), , 1871-1877.
Dietrich, C., Swingley, D., & Werker, J.F. (2007). Native language governs interpretation of salient speech sound differences at 18 months. Proceedings of the National Academy of Sciences of the US, 16027-16031.
Dillon, B., Dunbar, E., & Idsardi, B. (2011 ms). A single stage approach to learning phonological categories: Insights from Inuktitut. University of Maryland, College Park and University of Massachusetts, Amherst.
Feldman, N., Griffiths, T., and Morgan, J. (2009). Learning phonetic categories by learning a lexicon. Proceedings of the 31st Annual Conference on Cognitive Science.
Feldman, N., Myers, E., White, K., Griffiths, T., & Morgan, J. (2011). Learners use word-level statistics in phonetic category acquisition. Proceedings of the 35th Boston University Conference on Language Development.
Finn, A. & Hudson Kam, C. (2008). The curse of knowledge: First language knowledge impairs adult learners’ use of novel statistics for word segmentation. Cognition, 108, 477-499.
Fleck, M. (2008). Lexicalized phonotactic word segmentation. In 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., Arnon, I., Tily, H., & Goldwater, S. (2010). Beyond Transitional Probabilities: Human Learners Impose a Parsimony Bias in Statistical Word Segmentation. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Frank, M., Goldwater, S., Griffiths, T., & Tenenbaum, J. (2010). Modeling human performance in statistical word segmentation. Cognition, 117(2), 107-125.
Frank, M., Goodman, N., & Tenenbaum, J. (2009). Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning. Psychological Science, 20(5), 578-585.
Freudenthal, D., Pine, J., & Gobet, F. (2010). Explaining quantitative variation in the rate of Optional Infinitive errors across languages: A comparison of MOSAIC and the Variational Learning Model. Journal of Child Language, 37(3), 643-669.
Gambell, T. & Yang, C. (2006). Word Segmentation: Quick but not dirty. Manuscript, Yale University.
Gerken, L. (2006). Decisions, decisions: infant language learning when multiple generalizations are possible. Cognition, 98, B67-B74.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2007). Distributional cues to word segmentation: Context is important. Proceedings of the 31st Boston University Conference on Language Development.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1), 21-54.
Gomez, R. & Gerken, L. (2000). Infant artificial language learning and language acquisition.Trends in Cognitive Sciences, 4(5), 178-186.
Goodluck, H. (2010). First language acquisition. Wiley Interdisciplinary Reviews: Cognitive Science, n/a. doi: 10.1002/wcs.95.
Hadley, P., Rispoli, M., Fitzgerald, C., & Bahnsen, A. (2011). Predictors of Morphosyntactic Growth in Typically Developing Toddlers: Contributions of Parent Input and Child Sex. Journal of Speech, Language, & Hearing Research, 54(2), 549-566.
Hewlett, D. & Cohen, P. (2009). Bootstrap voting experts. In Proceedings of the twenty-first international joint conference on artificial intelligence (IJCAI-09) 1071-1076.
Hsu, A. & Chater, N. (2010). The Logical Problem of Language Acquisition: A Probabilistic Perspective. Cognitive Science, 34, 972-1016.
Hudson Kam, C. & Newport, E.. (2009). Getting it right by getting it wrong: When learners change languages. Cognitive Psychology, 59, 30-66.
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.
Johnson, E. & Tyler, M. (2010). Testing the limits of statistical learning forwWord segmentation. Developmental Science, 13(2),339-345.
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.
Kam, X., Stoyneshka, I., Tornyova, L., Fodor, J., & Sakas, W. (2008). Bigrams and the Richness of the Stimulus. Cognitive Science, 32, 771-787.
Kemp, C., Perfors, A., Tenenbaum, J. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Kidd, C., Piantadosi, S., & Aslin, R. (2010). The Goldilocks Effect: Infants’ preference for stimuli that are neither too predictable nor too surprising. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Knight, K. Bayesian Inference with Tears. Manuscript downloaded from http://www.isi.edu/~knight/.
Lasnik, H. & Lohndal, T. (2010). Government–binding/principles and parameters theory. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 40–50. doi: 10.1002/wcs.35.
Legate, J. & Yang, C. (2002). Empirical re-assessment of stimulus poverty arguments. The Linguistic Review, 19, 151-162.
Legate, J. & Yang, C. (2007). Morphosyntactic learning and the development of tense. Language Acquisition, 14(3), 315-344.
Legate, J., & Yang, C. (2011). Assessing Child and Adult Grammar. To appear in R. Berwick & M., Piatelli-Palmarini (eds.), Rich Languages from Poor Inputs: In Honor of Carol Chomsky.
Lidz, J. (2010). Language Learning and Language Universals. Biolinguistics, 4(2-3), 201-217.
Lidz, J., Waxman, S., & Freedman, J. (2003). What infants know about syntax but couldn’t have learned: experimental evidence for syntactic structure at 18 months. Cognition, 89, B65-B73.
Liebbrandt, R. & Powers, D. (2010). Frequent Frames as Cues to Part-of-Speech in Dutch: Why Filler Frequency Matters. Proceedings of the 32nd Annual Meeting of the Cognitive Science Society.
Lightfoot, D. (2010). Language acquisition and language change. Wiley Interdisciplinary Reviews: Cognitive Science, 1, 677–684. doi: 10.1002/wcs.39.
Marr, D. (1982). Vision. San Francisco: W.H. Freeman, pp. 3-43.
Maye, J., Werker, J., & Gerken, L. (2002). Infant sensitivity to distributional information can affect phonetic discrimination. Cognition, 82, , B101-B111.
McInnes, F., & Goldwater, S. (2011). Unsupervised extraction of recurring words from infant-directed speech Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin, TX.
Medina, T., Snedecker, J., Trueswell, J., & Gleitman, L. (2011). How words can and cannot be learned by observation Proceedings of the National Academy of Sciences, 1089014-9019.
Mintz, T. (2003). Frequent frames as a cue for grammatical categories in child directed speech.Cognition, 90, 91-117.
Mintz, T. (2006). Finding the verbs: distributional cues to categories available to young learners. In K. Hirsh-Pasek & R. M. Golinkoff (Eds.), Action Meets Word: How Children Learn Verbs (pp. 31-63). New York: Oxford University Press.
Mitchener, G. & Becker, M. (2011). Computational Models of Learning the Raising-Control Distinction. Research on Language and Computation, 8(2), 169-207.
Nevins, A. (2010). Two Case Studies in Phonological Universals: A View from Artificial Grammars. Biolinguistics, 4(2-3), 218-233.
Onnis, L., Monaghan, P., Richmond, K., & Chater, N. (2005). Phonology impacts segmentation in online speech processing. Journal of Memory and Language, 53, 225-237.
Pearl, L. (2008). Putting the Emphasis on Unambiguous: The Feasibility of Data Filtering for Learning English Metrical Phonology. In Chan, H., Jacob, H., and Kapia, E (eds.), BUCLD 32: Proceedings of the 32nd annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press, 390-401.
Pearl, L. (2009). Learning English Metrical Phonology: When Probability Distributions Are Not Enough. In Jean Crawford, Koichi Otaki, and Masahiko Takahashi (eds.), Proceedings of the 3rd Conference on Generative Approaches to Language Acquisition North America (GALANA 2008), Somerville, MA: Cascadilla Press, 200-211.
Pearl, L. (2010). Computational Models of Language Acquisition. In E. Blom & S. Unsworth (eds), Experimental Methods in Language Acquisition Research, John Benjamins.
Pearl, L. (2010 ms). When unbiased probabilistic learning is not enough: Acquiring a parametric system of metrical phonology. University of California, Irvine.
Pearl, L. & Goldwater, S. (2010 ms). Statistical Learning, Inductive Bias, and Bayesian Inference in Language Acquisition. University of California, Irvine and University of Edinburgh.
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.
Pearl, L., Goldwater, S., & Steyvers, M. (2011). Online Learning Mechanisms for Bayesian Models of Word Segmentation. Research on Language and Computation, 8(2), 107-132.
Pearl, L. & Lidz, J. (2009). When domain-general learning fails and when it succeeds: Identifying the contribution of domain-specificity. Language Learning & Development, 5(4), 235-265.
Pearl, L. & Lidz, J. (2010 ms.) Parameters in Language Acquisition. University of California, Irvine & University of Maryland, College Park.
Pearl, L., & Mis, B. (2011). How Far Can Indirect Evidence Take Us? Anaphoric One Revisited, In L. Carlson, C. Hölscher, & T. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 879-884. Austin, TX: Cognitive Science Society.
Pearl, L., & Mis, B. (2011 submitted). What Indirect Evidence Can Tell Us About Universal Grammar: Anaphoric One Revisited. University of California, Irvine.
Pelham, S. (2011). The input ambiguity hypothesis and case blindness: an account of cross-linguistic and intra-linguistic differences in case errors. Journal of Child Language, 38, 235-272.
Perfors, A., Tenenbaum, J., Griffiths, T., & Xu, F., (2010 ms). A tutorial introduction to Bayesian models of cognitive development. University of Adelaide, Massachusetts Institute for Technology, and University of California, Berkeley.
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.
Perfors, A., Tenenbaum, J., & Regier, T. (2011). The learnability of abstract syntactic principles. Cognition, 118, 306-338.
Perfors, A., Tenenbaum, J., Griffiths, T., & Xu, F. (2011). A tutorial introduction to Bayesian models of cognitive development. Cognition, 120, 302-321.
Pinker, S. (2004). Clarifying the logical problem of language acquisition. Journal of Child Language, 31, 949-953.
Pullum, G. & Scholz, B. (2002). Empirical assessment of stimulus poverty arguments.The Linguistic Review, 19, 9-50.
Ramscar, M., Dye, M., Klein, J., Aguirre, N., Ruiz, L., & Saddat, L. (2011). Informativity versus logic: Children and adults take different approaches to word learning. Proceedings of the 33rd Annual Conference of the Cognitive Science Society. Austin, TX.
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