Bibliography

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T1: Lexical acuiqisition

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[1] D. R. Bailey, J. A. Feldman, S. Narayanan, and G. Lakoff. Modeling Embodied Lexical Development. In Proceedings of the 19th Cognitive Science Society Conference, 1997.
[ Paper ]
[2] P. Bloom. How Children Learn the Meanings of Words. MIT Press, Cambridge, Mass., 2000.
[3] B. Boguraev and J. Pustejovsky, editors. Corpus Processing for Lexical Acquisition. MIT Press, 1996.
[4] K. Ehrlich and W. J. Rapaport. A Computational Theory of Vocabulary Expansion. Technical Report 95-15, State University of New York at Buffalo, March 1995.
[ Paper ]
[5] E. Gaussier. Unsupervised learning of derivational morphology from inflectional lexicons. In Proceedings of ACL-99, 1999.
[ Paper ]
[6] L. Gleitman. The Structural Sources of Verb Meanings. Language Acquisition, pages 3-55, 1990.
[7] J. Goldsmith. Unsupervised Learning of the Morphology of a Natural Language. Computational Linguistics, June 2001.
[ Paper ]
[8] P. Gordon. Evaluating the Semantic Categories Hypothesis: the Case of the Count/Mass Distinction. Cognition, 20:209-242, 1985.
[9] P. Gordon. Level-ordering in Lexical Development. Cognition, 21:73-93, 1986.
[10] A. L. Gorin, S. E. Levinson, A. N. Gertner, and E. Goldman. Adaptive Acquisition of Language. Computer Speech and Language, 5:101-132, 1991.
[11] P. M. Hastings and S. L. Lytinen. Objects, Actions, Nouns and Verbs. In Proceedings of the 16th Cognitive Science Society Conference, 1994.
[12] Carl de Marcken. The Unsupervised Acquisition of a Lexicon from Continuous Speech. AI Memo 1558, AI Lab, Center for Biological and Computational Learning, and Dept. of Brain and Cognitive Sciences, MIT, November 1995.
[ Paper ]
[13] D. Roy. A computational model of word learning from multimodal sensory input. In Proceedings of the 3rd International Conference of Cognitive Modeling (ICCM-2000), Groningen, Netherlands, March 2000.
[ Paper ]
[14] D. Roy. Grounded Speech Communication. In Proceedings of the Sixth International Conference on Spoken Language Processing (ICSLP-2000), Beijing, China, October 2000.
[ Paper ]
[15] A. Sankar and A. Gorin. Adaptive language acquisition in a multisensory device. In R. Mammone, editor, Artificial Neural Networks for Speech and Vision, pages 325-356. Chapman & Hall, 1993.
[16] C. A. Thompson and R. J. Mooney. Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces. In Proceedings of AAAI-99, 1999.
[ Paper ]
[17] A. L. Woodward and E. M. Markman. Early Word Learning. In W. Damon, D. Kuhn, and R. Siegler, editors, Handbook of Child Psychology: Cognition, Perception and Language, volume 2. Wiley & Sons, New York, 5 edition, 1998.

T2: Grammar Induction

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[1] P. J. Angeline, G. M. Saunders, and J. B. Pollack. An Evolutionary Algorithm that Constructs Recurrent Neural Networks. IEEE Transactions on Neural Networks, 5:54-65, 1994.
[2] D. Angluin. Inductive Inference of Formal Languages from Positive Data. Information and Control, 45(2), 1980.
[3] D. Angluin. Learning Regular Sets from Queries and Counterexamples. Information and Computation, 75:87-106, 1987.
[4] D. Angluin. Negative Results for Equivalence Quieries. Machine Learning, 5, 1990.
[5] R. C. Carrasco and J. Oncina. Learning Stochastic Regular Grammar by Means of a State Merging Method. In R. C. Carrasco and J. Oncina, editors, Proceedings of the 2nd International Colloquium on Grammatical Inference (ICGI-1994), pages 139-152, 1994.
[6] E. Charniak. Tree-bank grammars. Proceedings of AAAI-96, 1996.
[ Paper ]
[7] L.-V. Ciortuz. Object-oriented Inferences in a Logical Framework for Feature Grammars. In R. C. Carrasco and J. Oncina, editors, Proceedings of the 2nd International Colloquium on Grammatical Inference (ICGI-1994), Alicante, Spain, September 1994. Springer-Verlag.
[8] F. Coste and D. Fredouille. Efficient Ambiguity Detection in C-NFA. In Proceedings of the 5th International Colloquium on Grammatical Inference (ICGI-2000), Lisbon, Portugal, September 2000. Springer-Verlag.
[9] C. Culy. The Complexity of the Vocabulary of Bambara. Linguistics and Philosophy, 8:345-351, 1985.
[10] S. Das, C. Giles, and G. Z. Sun. Learning Context Free Grammars: Capabilities and Limitations of a Recurrent Neural Network with an External Stack Memory. In Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society, pages 791-795, 1992.
[11] P. Dupont, L. Miclet, and E. Vidal. What is the Search Space of the Regular Inference? In R. C. Carrasco and J. Oncina, editors, Proceedings of the 2nd International Colloquium on Grammatical Inference (ICGI-1994), pages 25-37, Alicante, Spain, 1994.
[12] K. G. Emerald, K. G. Subramanian, and D. G. Thomas. Inferring Subclasses of Contextual Languages. In Proceedings of the 5th International Colloquium on Grammatical Inference (ICGI-2000), Lisbon, Portugal, September 2000. Springer-Verlag.
[13] M. Gavaldà. Interactive Grammar Repair. In Proceedings of the Workshop on Automated Acquisition of Syntax and Parsing of the 10th European Summer School in Logic, Language and Information (ESSLLI-1998), Saarbricken, German, August 1998.
[ Paper ]
[14] M. Gavaldà. Epiphenomenal Grammar Acquisition with GSG. In Proceedings of the Workshop on Conversational Systems of the 6th Conference on Applied Natural Language Processing and the 1st Conference of the North American Chapter of the Association for Computational Linguistics (ANLP/NAACL-2000), Seattle, U.S.A, May 2000.
[ Paper ]
[15] M. Gavaldà. Growing Semantic Grammars. PhD thesis, Language Technologies Institute, School of Computer Science, Carnegie Mellon University, August 2000.
[ Paper ]
[16] C. Giles, D. Chen, H. Miller, and G. Sun. Second-order Recurrent Neural Networks for Grammatical Inference. In Proceedings of the International Joint Conference on Neural Networks, volume 2, pages 273-281, 1991.
[17] J. Giordano. Inference of Context-free Grammars by Enumeration: Structural Containment as an Ordering Bias. In R. C. Carrasco and J. Oncina, editors, Proceedings of the 2nd International Colloquium on Grammatical Inference (ICGI-1994), pages 212-221, Alicante, Spain, 1994.
[18] E. M. Gold. Language Identification in the Limit. Information and Control, 10(5), 1967.
[19] E. M. Gold. Complexity of Automaton Identification from Given Data. Information and Control, 37:302-320, 1978.
[20] J. E. Hopcroft and J. D. Ullman. Introduction to Automata Theory, Languages and Computation. Addison-Wesley, 1979.
[21] R. Hwa. Supervised Grammar Induction using Training Data with Limited Constituent Information. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, June 1999.
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[22] A. Itai. Learning Morphology - Practice Makes Good. In R. C. Carrasco and J. Oncina, editors, Proceedings of the 2nd International Colloquium on Grammatical Inference (ICGI-1994), Alicante, Spain, September 1994. Springer-Verlag.
[23] D. Kazakov. Unsupervised Learning of Naive Morphology with Genetic Algorithms. In W.; Daelemans, Antal van den; Bosch, and T. Weijters, editors, Workshop Notes of the ECML/MLnet Workshop on Empirical Learning of Natural Language Processing Tasks, Prague, Czech, April 1997.
[ Paper ]
[24] M. Kifer, G. Lausen, and J. Wu. Logical Foundations of Object-oriented and Frame-based Languages. Journal of Association for Computing Machinery, May 1995.
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[25] M. Lankhorst. A Genetic Algorithm for Induction of Nondeterministic Pushdown Automata. Cs-r 9502, University of Groningen, The Netherlands, 1995.
[26] L. Lee. Learning of Context-free Languages: A Survey of the Literature. Technical Report TR-12-96, Center for Research in Computing Technology, Harvard University, Cambridge, MA, 1996.
[ Paper ]
[27] Carl de Marcken. On the Unsupervised Induction of Phrase-structure Grammars. In Proceedings of the 3rd Workshop on Very Large Corpora. SIGDAT and SIGNLL, ACL, 1995.
[ Paper ]
[28] J. L. Morgan. From simple input to complex grammar. MIT Press, 1986.
[29] J. Oncina and P. Garcia. Inferring Regular Languages in Polunomial Update Time. In N. Perez, editor, Pattern Recognition and Image Analysis, pages 49-61. World Scientific, 1992.
[30] R. Parekh and V. Honavar. An Incremental Interactive Algorithm for Regular Grammar Inference. In L. Miclet and C. Higuera, editors, Proceedings of the 3rd International Colloquium on Grammatical Inference (ICGI-1996), Montpellier, France, 1996.
[31] R. Parekh and V. Honavar. Grammar Inference, Automata Induction, and Language Acquisition. In R. Dale, H. Moisl, and H. Somers, editors, A Handbook of Natural Language Processing: Techniques and Applications for the Processing of Language as Text. New York: Marcel Dekker, 2000.
[ Paper ]
[32] K. Probst, R. Brown, J. Carbonell, A. Lavie, L. Levin, and E. Peterson. Design and Implementation of Controlled Elicitation for Machine Translation of Low-density Languages. In Proceedings of the MT2010workshop at MT Summit 2001, 2001.
[ Paper ]
[33] K. Probst and L. Levin. Challenges in Automated Elicitation of a Controlled Bilingual Corpus. In Proceedings of TMI 2002, 2002.
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[34] Y. Sakakibara. Efficient Learning of Context-free Grammars from Positive Structural Examples. Information and Computation, 97, 1992.
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[35] Y. Sakakibara and H. Muramatsu. Learning Context-free Grammars from Partially Structured Examples. In Proceedings of the 5th International Colloquium on Grammatical Inference (ICGI-2000), Lisbon, Portugal, September 2000. Springer-Verlag.
[36] S. Shieber. Evidence Against the Context-freeness of Natural Languages. Linguistics and Philosophy, 8:333-343, 1985.
[37] H. Siegelmann and C. Giles. The Complexity of Language Recognition by Neural Networks. Neurocomputing, 15:327-345, 1997.
[38] A. Stolcke. Bayesian Learning of Probabilistic Language Models. PhD thesis, University of California at Berkeley, 1994.
[ Paper ]
[39] A. Stolcke and S. Omohundro. Inducing Probablistic Grammars by Bayesian Model Merging. In R. C. Carrasco and J. Oncina, editors, Proceedings of the 2nd International Colloquium on Grammatical Inference (ICGI-1994), Alicante, Spain, September 1994. Springer-Verlag.
[40] K. Vanlehn and W. Ball. A Version Space Approach to Learning Context-free Grammars. Machine Learning, 2:39-74, 1987.
[41] J. M. Zelle. Using Inductive Logic Programming to Automate the Construction of Natural Language Parsers. PhD thesis, University of Texas, Austin, TX, 1995.
[ Paper ]
[42] J. M. Zelle and R. J. Mooney. Learning semantic grammars with constructive inductive logic programming. In Proceedings of the Eleventh National Conference on Artificial Intelligence, pages 817-822. AAAI Press/MIT Press, 1993.
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T3: Discourse/pragmatics learning

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[1] J. Chu-Carroll. A Statistical Model for Discourse Act Recognition in Dialogue Interactions. 1998 aaai spring symposium: Applying machine learning to discourse processing, AAAI, 1998.
[2] N. Green and J. F. Lehman. An Application of Explanation-Based Learning to Discourse Generation and nterpretation. 1998 aaai spring symposium: Applying machine learning to discourse processing, AAAI, 1998.
[3] D. Hardt. Improving Ellipsis Resolution with Transformation-Based Learning. 1998 aaai spring symposium: Applying machine learning to discourse processing, AAAI, 1998.
[4] D. Lin. Automatic Retrieval and Clustering of Similar Words. In COLING-ACL98, Montreal, Canada, August 1998.
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[5] M. Poesio, Sabine Schulte im. Walde, and C. Brew. Lexical Clustering and Definite Description Interpretation. 1998 aaai spring symposium: Applying machine learning to discourse processing, AAAI, 1998.
[6] K. Samuel, S. Carberry, and K. Vijay-Shanker. Computing Dialogue Acts from Features with Transformation-Based Learning. 1998 aaai spring symposium: Applying machine learning to discourse processing, AAAI, 1998.
[7] A. Stolcke, K. Ries, N. Coccaro, E. Shriberg, R. Bates, D. Jurafsky, P. Taylor, R. Martin, C. Van Ess-Dykema, and M. Meteer. Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech. Computational Linguistics, 26(3):339-373, September 2000.
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[8] J. Wiebe. Learning Subjective Adjectives from Corpora. In the 17th National Conference on Artificial Intelligence (AAAI-2000), Austin, Texas, July 2000.
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T4: Knowledge representation/inferences for LA

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[1] S. Dzeroski, J. Cussens, and S. Manandhar. An Introduction to Inductive Logic Programming and Learning Language in Logic. In J. Cussens and S. Dzeroski, editors, Proceedings of Learning Language in Logic, LLL-99, pages 3-35, Bled, Slovenia, 30 June 1999.
[2] V. Haarslev and R. Möller. High Performance Reasoning with Very Large Knowledge Bases: A Practical Case Study. In Seventeenth International Joint Conference on Artificial Intelligence, Seattle, WA, August 2001.
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[3] I. Horrocks, U. Sattler, and S. Tobies. Practical Reasoning for Very Expressive Description Logics. Logic Journal of the IGPL, 8(3):239-263, 2000.
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[4] A. N. Kaplan and L. K. Schubert. A Computational Model of Belief. Artificial Intelligence, 120:119-160, 2000.
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[5] R. Mooney. Learning for Semantic Interpretation: Scaling Up without Dumbing Down. In J. Cussens and S. Dzeroski, editors, Proceedings of Learning Language in Logic, LLL-99, pages 57-66, Bled, Slovenia, 30 June 1999.
[6] H. Ng and R. Mooney. On the Role of Coherence in Abductive Explanation. Proceedings of AAAI-90, 1990.
[ Paper ]
[7] J. R. Quinlan, , and R. M. Cameron-Jones. FOIL: A Midterm Report. In Pavel B. Brazdil, editor, Proceedings of Machine Learning: ECML-93, pages 3-20, Vienna, Austria, 1993.
[ Paper ]
[8] W. J. Rapaport. How to Pass a Turing Test: Syntactic Semantics, Natural-Language Understanding, and First-Person Cognition. Special Issue on Alan Turing and Artificial Intelligence, Journal of Logic, Language, and Information, 9(4):467-490, October 2000.
[ Paper ]
[9] S. C. Shapiro. SNePS: A Logic for Natural Language Understanding and Commonsense Reasoning. In L. M. Iwanska and S. C. Shapiro, editors, Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language, pages 175-195. AAAI/MIT Press, July 2000.
[ Paper ]

P2: Cognitive science perspective

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[1] Angel M. Y., A. M. Y. Lin, and N. Akamatsu. The learnability and psychological processing of reading in Chinese and reading in English. In H. C. Chen, editor, Cognitive Processing of Chinese and Related Asian Languages, pages 369-387. The Chinese University Press, Hong Kong, 1997.
[2] E. Bates. On the nature and nurture of language. In R. Levi-Montalcini, D. Baltimore, R. Dulbecco, F. (Series Eds.) Jacob, E. Bizzi, P. Calissano, and V. (Vol. Eds.) Volterra, editors, Frontiere della biologia [Frontiers of biology]. The brain of homo sapiens. Giovanni Trecanni, Rome.
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[3] J. N. Bohannon III and L. Stanowicz. The Issue of Negative Evidence: Adult Responses to Children's Language Errors. Developmental Psychology, 24(5):684-689, 1988.
[4] Bénédicte de Boysson-Bardies. How Language Comes to Children: From Birth to Two Years. MIT Press, 1999.
[5] M. R. Brent, editor. Computational Approaches to Language Acquisition. MIT Press, 1997.
[6] P. A. Carpenter, A. Miyake, and Just. M. A. Language comprehension: Sentence and discourse processing. Annual Review of Psychology, 46:91-120, 1995.
[7] P. Gordon. Learnability and Feedback. Developmental Psychology, 26(2):217-220, 1990.
[8] K. Hirsh-Pasek and R. M. Golinkoff. The Origins of Grammar: Evidence from Early Language Comprehension. MIT Press, 1999.
[9] L. L. Holt, A. J. Lotto, and K. R. Kluender. Incorporating principles of general learning in theories of language acquisition. In M. Gruber, D. Higgins, K. S. Olson, and T. Wysocki, editors, Constraints, Acquisition of Spoken Language, Acquisition and the Lexicon, volume 34, pages 253-268. Chicago Linguistic Society, 1998.
[ Paper ]
[10] M. F. Joanisse and M. S. Seidenberg. Impairments in verb morphology after brain injury: A connectionist model. In Proceedings of the National Academy of Sciences of the United States of America, volume 96(13), pages 7592-7597, 1999.
[ Paper ]
[11] M. Mesulam. Large-scale neurocognitive networks and distributed processing for attention, language, and memory. Ann Neurol, 28:597-613, 1990.
[12] A. Pavlenko. New approaches to concepts in bilingual memory. Bilingualism, 2:209-230, 1999.
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[13] S. Pinker. Language Acquisition. In Osherson, editor, Language: An invitation to cognitive science (2nd ed.), pages 135-182. 1995.
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[14] J. Sougné, A. S. Nyssen, and V. De Keyser. Temporal Reasoning and Reasoning Theories A case study in anaesthesiology. Psychologica Belgica, 33:311-328, 1993.
[15] I. Taylor. Psycholinguistic Reasons for Keeping Chinese Characters in Korean and Japanese. In H. C. Chen, editor, Cognitive Processing of Chinese and Related Asian Languages, pages 299-319. The Chinese University Press, Hong Kong, 1997.
[16] S. H. Weber and A. Stolcke. L0: A Testbed for Miniature Language Acquisition. Technical report, International Computer Science Institute, Berkeley, CA, July 1990.
[17] H. Yang and D-l Peng. The Learning and Naming of Chinese Characters of Elementary School Children. In H. C. Chen, editor, Cognitive Processing of Chinese and Related Asian Languages, pages 323-346. The Chinese University Press, Hong Kong, 1997.

P3: Linguistics perspective

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[1] J. Bresnan. Lexical-Functional Syntax. Blackwell, 2000.
[2] E. H. Nyberg. A non-deterministic, success-driven model of parameter setting in language acquisition. PhD thesis, Carnegie Mellon University, Pittsburgh, PA 15213, May 1992.
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[3] B. Tesar and P. Smolensky. Learning Optimality-Theoretic grammars. In A. Sorace, C. Heycock, and R. Shillcock, editors, Language Acquisition: Knowledge Representation and Processing. Elsevier, 1998.
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