We will refer to selections from the following books, in addition to the articles below:
Aslin, R. & Newport, E. (forthcoming). Statistical Learning: From Acquiring Specific Items to Forming General Rules. Current Directions in Psychological Science.
Baker, M. (2008). The Macroparameter in a Microparametric World. In T. Biberauer (ed.), The Limits of Syntactic Variation, John Benjamins, Amsterdam, 351-374.
Bergelson, E. & Swingley, D. (2012). At 6-9months, human infants know the meanings of many common nouns. Proceedings of the National Academy of Sciences of the USA, 109, 3253-3258.
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.
Borschinger, B. & Johnson, M. (2011). A Particle Filter algorithm for Bayesian Wordsegmentation. Proceedings of Australasian Language Technology Association Workshop, 10-18.
Brenchley, M. & Lobina, D. (2011). Disc: Re: Remarks by Noam Chomsky in London. The Linguist List, Nov 21, 2011.
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.
Daland, R. & Pierrehumbert, J. (2011). Learning Diphone-Based Segmentation. Cognitive Science, 35, 119-155.
Davis, S.J., Newport, E.L., & Aslin, R.N. (2011). Probability learning in 10-month-old 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.
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.
Denison, S., Reed, C., & Xu, F. (forthcoming). The emergence of probabilistic reasoning in very young infants: Evidence from 4.5- and 6-month-olds. Developmental Psychology.doi: 10.1037/a0028278.
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, W. (forthcoming). A single stage approach to learning phonological categories: insights from inuktitut. Cognitive Science.
Elsner, M., Goldwater, S., & Eisenstein, J. (2012). Bootstrapping a Unified Model of Lexical and Phonetic Acquisition. Proceedings of the 50th Annual Meeting of the Association of Computational Linguistics.
Fazly, A., Alishahi, A., & Stevenson, S. (2010). A probabilistic computational model of cross-situational word learning. Cognitive Science, 34(6), 1017-1063.
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., Griffiths, T., Goldwater, S., & Morgan, J. (2012). A role for the developing lexicon in phonetic category acquisition. Manuscript, University of Maryland, University of California at Berkeley, University of Edinburgh, and Brown University. Note: Please do not cite without permission from Naomi Feldman.
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. 2012. Computational models of early language acquisition. Manuscript, Stanford University. Note: Please do not cite without permission from Michael Frank.
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.
Frank, M. C., Tenenbaum, J. B., & Fernald, A. (forthcoming). Social and discourse contributions to the determination of reference in cross-situational word learning. Language Learning, and Development.
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.
Gagliardi, A., Bennett, E., Lidz, J., & Feldman, N. (2012). Children's Inferences in Generalizing Novel Nouns and Adjectives. In N. Miyake, D. Peebles, & R. Cooper (Eds.), Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 354-359.
Gagliardi, A., Feldman, N., & Lidz, J. (2012). When Suboptimal Behavior is Optimal and Why: Modeling the Acquisition of Noun Classes in Tsez. In N. Miyake, D. Peebles, & R. Cooper (Eds.), Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 360-365.
Gagliardi, A. & Lidz, J. (2012). Separating Input from Intake: Acquiring Noun Classes in Tsez. Manuscript, University of Maryland.
Gagliardi, A., Mease, T., & Lidz, J. (2012). U-shaped development in the acquisition of filler-gap dependencies: Evidence from 15- and 20-month-olds. Manuscript, University of Maryland.
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.
Gopnik, A. & Schultz, L. (2007). Introduction. In A. Gopnik & L. Schultz (Eds.), Causal learning: Psychology, philosophy, and computation. New York: Oxford University Press.
Gopnik, A. & Tenenbaum, J. (2007). Bayesian networks, Bayesian learning and cognitive development. Developmental Science, 10(3), 281-287.
Graf Estes, L., Edwards J., & Saffran, J. (2011). Phonotactic Constraints on Infant Word Learning. Infancy, 16(2), 180-197.
Gweon, H., J. B. Tenenbaum, & L. E. Schulz. (2010). Infants Consider Both the Sample and the Sampling Process in Inductive Generalization. Proceedings of the National Academy of Sciences 107.20, 9066–9071.
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/.
Kowalski, A. & Yang, C. (2012). Verb Islands in Child and Adult Language. In A. Biller, E. Chung, & A. Kimball (Eds.), BUCLD: Proceedings of the 36th annual Boston University Conference on Language Development., 281-289.
Kurumada, C., Meylan, S., & Frank, M. (2012). Zipfian frequency distributions facilitate word segmentation in context. Maunscript, Stanford University.
Lany, J. & Saffran, J. (2011). Interactions between statistical and semantic information in infant language development. Developmental Science, 14, 1207-1219.
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.
Lew-Williams, C., Pelucchi, B., & Saffran, J. (2011). Isolated words enhance statistical language learning in infancy.Developmental Science, 14(6), 1323-1329.
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.
Lignos, C. (2011). Modeling Infant Word Segmentation. Proceedings of the Fifteenth Conference on Cpmputational Natural Language Learning, 29-38.
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.
Mersad, K. & Nazzi, T. (2012). When Mommy Comes to the Rescue of Statistics: Infants Combine Top-Down and Bottom-Up Cues to Segment Speech. Language Learning and Development, 8(3), 303-315.
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.
Monahan, P. & Idsardi, W. (2010). Auditory sensitivity to formant ratios: Toward an account of vowel normalisation. Language and Cognitive Processes, 25(6), 808-839.
Nevins, A. (2010). Two Case Studies in Phonological Universals: A View from Artificial Grammars. Biolinguistics, 4(2-3), 218-233.
O'Grady, W. (2012). Three factors in the design and acquisition of language. Wiley Interdisciplinary Reviews: Cognitive Science, 3, 493-499. doi: 10.1002/wcs.1188.
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. (forthcoming). Statistical Learning, Inductive Bias, and Bayesian Inference in Language Acquisition. In J. Lidz, W. Snyder, & C. Pater (eds), The Oxford Handbook of Developmental Linguistics.
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. (2012). Induction problems, indirect positive evidence, and Universal Grammar: Anaphoric one Revisited. Manuscript, University of California, Irvine.
Pearl, L. & Sprouse, J. (forthcoming). Computational Models of Acquisition for Islands, In J. Sprouse & N. Hornstein (eds), Experimental Syntax and Islands Effects. Cambridge University Press.
Pearl, L. & Sprouse, J. (forthcoming). Syntactic islands and learning biases: Combining experimental syntax and computational modeling to investigate the language acquisition problem. Language Acquisition.
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. (2012). Bayesian Models of Cognition: What's Built In After All? Philosophy Compass, 7(2), 127-138.
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.
Phillips, C. (forthcoming). On the Nature of Island Constraints II: Language Learning and Innateness.In J. Sprouse & N. Hornstein (Eds.), Experimental Syntax and Island Effects. Cambridge University Press.
Phillips, L. & Pearl, L. (2012). "Less is More" in Bayesian word segmentation: When cognitively plausible learners outperform the ideal, In N. Miyake, D. Peebles, & R. Cooper (eds), Proceedings of the 34th Annual Conference of the Cognitive Science Society, 863-868. Austin, TX: Cognitive Science Society.
Pinker, S. (2004). Clarifying the logical problem of language acquisition. Journal of Child Language, 31, 949-953.
Pullum, G. (2011). Disc: Remarks by Noam Chomsky in London. The Linguist List, Nov 19, 2011.
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.
Roseberry, S., Richie, R., Hirsh-Pasek, K., Golinkoff, R., & Shipley, T. (2011). Babies Catch a Break: 7- to 9-Month-Olds Track Statistical Probabilities in Continuous Dynamic Events. Psychological Science, 22(11),, 1422-1424.
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.
Sondregger, M. (2008). Infant word segmentation: a basic review. Manuscript, University of Chicago.
Stumper, B., Bannard, C., Lieven, E., & Tomasello, M. (2011). "Frequent Frames" in German Child-Directed Speech: A Limited Cue to Grammatical Categories. Cognitive Science, 35, 1190-1205.
Swingley, D. (2005). Statistical clustering and the contents of the infant vocabulary. Cognitive Psychology, 50, 86-132.
Swingley, D. (2012). Cognitive Development in Language Acquisition. Language Learning and Development, 8, 1-3.
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.
Viau, J. & Lidz, J. (2011). Selective Learning in the Acquisition of Kannada Ditransitives. Language, 87, 679-714.
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.
Xu, F., & Tenenbaum, J. (2007). Sensitivity to sampling in Bayesian word learning Developmental Science, 10(3), 288-297.
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.
Yang, C. (2010). Who's Afraid of George Kingsley Zipf? Manuscript, University of Pennsylvania.
Yang, C. (2011). A Statistical Test for Grammar. Proceedings of the 2nd Workshop on Cognitive Modeling and Computational Linguistics, 30-38.
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.
Baker, M. (2008). The Macroparameter in a Microparametric World. In T. Biberauer (ed.), The Limits of Syntactic Variation, John Benjamins, Amsterdam, 351-374.
Bergelson, E. & Swingley, D. (2012). At 6-9months, human infants know the meanings of many common nouns. Proceedings of the National Academy of Sciences of the USA, 109, 3253-3258.
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.
Borschinger, B. & Johnson, M. (2011). A Particle Filter algorithm for Bayesian Wordsegmentation. Proceedings of Australasian Language Technology Association Workshop, 10-18.
Brenchley, M. & Lobina, D. (2011). Disc: Re: Remarks by Noam Chomsky in London. The Linguist List, Nov 21, 2011.
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.
Daland, R. & Pierrehumbert, J. (2011). Learning Diphone-Based Segmentation. Cognitive Science, 35, 119-155.
Davis, S.J., Newport, E.L., & Aslin, R.N. (2011). Probability learning in 10-month-old 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.
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.
Denison, S., Reed, C., & Xu, F. (forthcoming). The emergence of probabilistic reasoning in very young infants: Evidence from 4.5- and 6-month-olds. Developmental Psychology.doi: 10.1037/a0028278.
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, W. (forthcoming). A single stage approach to learning phonological categories: insights from inuktitut. Cognitive Science.
Elsner, M., Goldwater, S., & Eisenstein, J. (2012). Bootstrapping a Unified Model of Lexical and Phonetic Acquisition. Proceedings of the 50th Annual Meeting of the Association of Computational Linguistics.
Fazly, A., Alishahi, A., & Stevenson, S. (2010). A probabilistic computational model of cross-situational word learning. Cognitive Science, 34(6), 1017-1063.
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., Griffiths, T., Goldwater, S., & Morgan, J. (2012). A role for the developing lexicon in phonetic category acquisition. Manuscript, University of Maryland, University of California at Berkeley, University of Edinburgh, and Brown University. Note: Please do not cite without permission from Naomi Feldman.
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. 2012. Computational models of early language acquisition. Manuscript, Stanford University. Note: Please do not cite without permission from Michael Frank.
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.
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