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'''The Basics of Efficiency'' | |
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* Sheldon Ross. 2010. A First Course in Probability. Eigth Edition. Section 9.3 "Surprise, Uncertainty, and Entropy", pages 425-429. [[attachment:Ross10.pdf pdf]], see also [http://onlinestatbook.com/] | * Sheldon Ross. 2010. A First Course in Probability. Eigth Edition. Section 9.3 "Surprise, Uncertainty, and Entropy", pages 425-429. see [http://onlinestatbook.com/] '''More than a Curious Phenomenon? Constant Entropy Rate''' |
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4. Class: Constant Entropy Rate Across Discourses | 4. Class: the Noisy Channel Theorem and Language |
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* Shannon, C.E. (1948). A Mathematical Theory of Communication. Mobile Computing and Communications Review, Volume 5, Number I. Reprinted from Bell System Technical Journal with corrections. [[attachment:shannon48.pdf pdf]] 5. Class: Constant Entropy Rate Across Discourses * Keller, F. (2004). The entropy rate principle as a predictor of processing effort: An evaluation against eye-tracking data. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Barcelona, pp. 317-324. [[attachment:keller04.pdf pdf]] |
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* Keller, F. (2004). The entropy rate principle as a predictor of processing effort: An evaluation against eye-tracking data. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Barcelona, pp. 317-324. [[attachment:keller04.pdf pdf]] | |
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5. Class: the Noisy Channel Theorem * Shannon, C.E. (1948). A Mathematical Theory of Communication. Mobile Computing and Communications Review, Volume 5, Number I. Reprinted from Bell System Technical Journal with corrections. [[attachment:shannon48.pdf pdf]] 6. Class: Zipf continued, early evidence from phonology and speech * Zipf 1935 (73-81, 109-121) and Zipf 1949 (98-108) on phonological change [[attachment:Zipf35-49_sound.pdf pdf]] * also covered: * Schuchardt, H. (1885) On sound laws: Against Neogrammarians. Translated by T. Vennemann and T.H. Wilbur. [[attachment:schuchardt1885.pdf pdf]] 7. Class: Functionalist Theories of Language Change * Bybee, J. * Bates, E. and MacWhinney, B. (1982) 8. Class: Frequency, Predictability and Word Duration |
'''Probability and Information in Online Language Production''' 6. Class: Frequency, Predictability and Word Duration |
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9. Class Word predictability and Word Pronunciation |
* Gahl, S. and Garnsey, S.M. (2004). Knowledge of grammar, knowledge of usage: Syntactic probabilities a ect pronunciation variation. Language, 80 (4), 748-775. * Gahl, S., Garnsey, S. M., Fisher, C., & Matzen, L. (2006). "That sounds unlikely": Syntactic probabilities affect pronunciation. Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1334-1339). 7. Class: Word predictability and Word Pronunciation |
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8. Class: Frequency, Predictability and Disfluency and Gesture * Shriberg, E., & Stolcke, A. (1996). Word predictability after hesitations: A corpus-based study. In Proceedings of ICSLP '96. * Cook, S. W., Jaeger, T. F., & Tanenhaus, M. K. (2009). Producing less preferred structures: More gestures, less Fluency. In Proceedings of the 31st conference of the Cognitive Science Society. Vancouver, BC. * also covered: * Clark, H. H., & Fox Tree, J. E. (2002). Using "uh" and "um" in spontaneous speech. Cognition, 84, 73-111. * Tily, H., Gahl, S., Arnon, I., Kothari, A., Snider, N., and Bresnan, J. (2009). Pronunciation reflects syntactic probabilities: Evidence from spontaneous speech. Language and Cognition, 1, XX-XX. 9. Class: Phonological and morphological reduction * Frank, A., & Jaeger, T.F. (2008, July). Speaking rationally: Uniform information density as an optimal strategy for language production. In The 30th annual meeting of the Cognitive Science Society (CogSci08) (p. 933-938). Washington, D.C. * Uriel Cohen Priva. 2008. Using Information Content to Predict Phone Deletion. Proceedings of the 27th West Coast Conference on Formal Linguistics, 90--98. 10. Class: Uniform Information Density and Morpho-Syntactic Production * Wasow, T., Jaeger, T.F., & Orr, D. (in press). Lexical variation in relativizer frequency. In H. Wiese & H. Simon (Eds.), Proceedings of the workshop on expecting the unexpected: Exceptions in grammar at the 27th annual meeting of the German Linguistic Association. Berlin and New York: Mouton de Gruyter. * parts of Jaeger, T.F. (submitted). Redundancy and reduction: Speakers manage syntactic information density. Cognitive Psychology. * also covered: * Jaeger, T.F. (submitted). Corpus-based research on language production: Information density a ffects the syntactic reduction of subject relatives. * Jaeger, T.F., Levy, R., and Ferreira, V. (in progress) * Norcliffe, E. and Jaeger, T.F. (in progress) 11. Class: Relative Entropy and Phrase omission * pp 127-138 and 145-151 (Experiment 3 and 4) in Resnik, P. (1996). Selectional constraints: An information-theoretic model and its computational realization. Cognition, 61 , 127-159. * Brown, P., & Dell, G.S. (1987). Adapting production to comprehension: The explicit mention of instruments. Cognitive Psychology, 19 (4), 441-472. * also covered: * Koenig, J.P., Mauner, G., and Bienvenue, B. (2003). Arguments for adjuncts. Cognition 89, 67-103. 12. Class: Information Density and Planning Beyond the Clause, Inference, Differences across Languages * Gomez Gallo, C., Jaeger, T. F., & Smyth, R. (2008, July). Incremental syntactic planning across clauses. In The 30th annual meeting of the Cognitive Science Society (CogSci08) (p. 845-850). Washington, D.C. * Hagoort, P., and Van Berkum, J. J. A. (2007). Beyond the sentence given. Philosophical Transactions of the Royal Society. Series B: Biological Sciences, 362, 801-811 * also covered: Gomez Gallo, C. 2010. PhD Thesis, University of Rochester. 13. Class: Uniform Information Density and Processing * Hale, J. (2001). A probabilistic earley parser as a psycholinguistic model. In Proceedings of the North American Association of Computational Linguistics. * Levy, R., & Jaeger, T.F. (2007). Speakers optimize information density through syntactic reduction. In B. Schlokopf, J. Platt, & T. Ho man (Eds.), Advances in neural information processing systems (NIPS) 19 (p. 849-856). Cambridge, MA: MIT Press. * Smith, N., & Levy, R. (2008, July). Optimal processing times in reading: A formal model and empirical investigation. In The 30th annual meeting of the Cognitive Science Society (CogSci08). Washington, D.C.. * could also be covered: * Levy, R. (2008). Expectation-based syntactic comprehension. Cognition, 106 (3), 1126-1177. 14. Class: Information Theory and Information Structure * Prince, Ellen F. 1992. The ZPG letter: Subjects, definiteness, and information-status. In S. Thompson and W. Mann, eds., Discourse Description: Diverse Analyses of a Fundraising Text. * pp 1-7 pf Rosenfeld, R. (1996). A maximum entropy approach to adaptive statistical language modelling. Computer speech and language 10(3),187- * Arnold, J. (I assume) CUNY talk I just reviewed that argues that givenness cannot be reduced to predictability/information density. * Tily & Piantadosi (2009). Refer efficiently: Use less informative expressions for more predictable meanings. Proceedings of the Workshop on Production of Referring Expressions, Cogsci 2009. * Also covered: * Excerpts from Givon, T. (1995). Functionalism and grammar. Amsterdam: John Benjamins. * Wasow, Perfors, and Beaver '''Computational Accounts and Mechanisms''' 15. Class: Connectionist Accounts of Production * Dell, G. S., Chang, F., & Grin, Z. M. (1999). Connectionist models of language production: Lexical access and grammatical encoding. Cognitive Science: A Multidisciplinary Journal, 23 (4), 517-542. * parts of Jaeger, T.F. (submitted). Redundancy and reduction: Speakers manage syntactic information density. Cognitive Psychology. * also covered: * Chang, F., Dell, G. S., & Bock, J. K. (2006). Becoming syntactic. Psychological Review, 113 (2), 234-272. * focusing on discussion of competition accounts, have another look at: Cook, S. W., Jaeger, T. F., & Tanenhaus, M. K. (2009). Producing less preferred structures: More gestures, less Fluency. In Proceedings of the 31st conference of the Cognitive Science Society. Vancouver, BC. '''Language Change: The Link between Processing and Grammar''' 16. Class: Zipf continued, early evidence from phonology and speech * Zipf 1935 (73-81, 109-121) and Zipf 1949 (98-108) on phonological change [[attachment:Zipf35-49_sound.pdf pdf]] * also covered: * Schuchardt, H. (1885) On sound laws: Against Neogrammarians. Translated by T. Vennemann and T.H. Wilbur. [[attachment:schuchardt1885.pdf pdf]] 17. Class: Functionalist Theories of Language Change * Bybee, J. (2002). Word frequency and context of use in the lexical di usion of phonetically conditioned sound change. Language Variation and Change, 14 (3), 261-290. * Bates, E. and MacWhinney, B. (1982) * also covered: * Bannard, M. * Arnon, I. and Snider, N. 18. Class: More on Optimal Lexica and Multiple Functional Pressures * Plotkin, J.B. and Nowak, M.A. (2000). Language evolution and information theory. Journal of Theoretical Bilogy 205(1), 147-159. * Gasser, M. (2004). The origins of arbitrariness in language. Annual Conference of the Cognitive Science Society, 26. * Piantadosi, Tily, Gibson (2009). The communicative lexicon hypothesis. Proceedings of Cogsci 2009. * also covered: * Graff, P. and Jaeger, T.F. (submitted). Locality and Feature Specificity in OCP Effects: Evidence from Aymara, Dutch, and Javanese. CLS. * Bi-directional OT approaches 19. Class: Entropy, Neighborhood, and Paradigms * Milin, P., Kuperman, V., Kostic, A. & Baayen, R.H. Paradigms bit by bit: an information- theoretic approach to the processing of inflection and derivation. In press in Blevins, James P. and Juliette Blevins (eds.), Analogy in Grammar: Form and Acquisition. Oxford: Oxford University Press. '''The End''' 20. Final Discussion and Wonders |
Computational Accounts of Production
Synopsis:
- Connectionist and spreading-activation models of language production (lexical and syntactic production, but with a focus on speech errors)
- Information theoretic models of incremental language production (phonetic, morphological, syntactic, and extra-syntactic preferences)
- Computational models of adaptation in language processing (implicit learning, ideal observer models)
We will start with a quick refresher (written for language researchers) on probability theory and information theory and then read a lot of papers on examples of how information content, entropy, etc. affect language production. The goal of the class would be to provide a thorough introduction to these topics, but also to discuss the short-comings of these types of accounts and their relation to other mechanistic accounts of language production.
Prerequisites
The seminar is intended for graduate students though I may consider advanced undergraduate students with a psycholinguistics background and strong interest. A very basic background in probability theory is assumed, but we'll go through the basics at the beginning of the class.
Requirements
This will be a reading/discussion seminar (not a lecture). So, even if you plan to audit I would appreciate if you do the readings (see webpage for more detail on requirements etc.).
Students who are taking the class for credits will have to prepare for every discussion. I plan to use the BlackBoard forum feature and students taking the class for credit will have to post 2 questions or comments at least 1 day before each class about the readings. Additionally, they will have to lead some discussions. There also will be a final project, which can be a discussion paper or a proposal for an experiment (or grant ;). The final write-up should be about 4-10pp.
Readings
There will be a lot readings for each day, but the goal is not for all of them to be read by everyone. Instead, we will have a short obligatory reading and then distribute additional readings across people in the class. Discussion leaders have to have read all of the papers.
Syllabus
This is a very rough draft of a syllabus. I am also blatantly stealing parts of a great class taught by Dan Jurafsky and Michael Ramscar at Stanford (Fall 2009). The list below is meant as a superset suggestion (covering all topics would take more than a semester). Please feel free to suggest additional topics or to tell me your favorites.
The Basics of Efficiency Zipf 1949 (1-22) and Zipf 1935 (20-39, 172-176) on the inverse frequency-form link Zipf35-49.pdf pdf John A. Goldsmith. 2007. Probability for linguists. Goldsmith07.pdf pdf Sheldon Ross. 2010. A First Course in Probability. Eigth Edition. Section 9.3 "Surprise, Uncertainty, and Entropy", pages 425-429. see [http://onlinestatbook.com/] Shannon, C.E. Prediction and entropy of printed English. Bell System Technical Journal, 30, 50-64. shannon51.pdf pdf Thomas M. Cover and Roger C. King. 1978. A Convergent Gambling Estimate of the Entropy of English. IEEE Transactions on Information Theory 24:4, 413-421. coverking78.pdf pdf Manin, D. 2006. Experiments on predictability of word in context and information rate in natural language. manin06.pdf pdf Genzel, D. and Charniak, E. (2002). Entropy rate constancy in text. In Proceedings of ACL-02. genzelcharniak02.pdf pdf Shannon, C.E. (1948). A Mathematical Theory of Communication. Mobile Computing and Communications Review, Volume 5, Number I. Reprinted from Bell System Technical Journal with corrections. shannon48.pdf pdf Keller, F. (2004). The entropy rate principle as a predictor of processing effort: An evaluation against eye-tracking data. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Barcelona, pp. 317-324. keller04.pdf pdf Qian, T. and Jaeger, T.F. (submitted). Entropy profiles in Language: A cross-linguistic investigation. Entropy. qianjaeger10.pdf pdf Qian, T. and Jaeger, T.F. (2009). Evidence for Efficient Language Production in Chinese. In CogSci Proceedings. qianjaeger09.pdf pdf Zipf 1935 (283-287) on speech rate (velocity of speech) Zipf35-49_sound.pdf pdf Pluymaekers, M., Ernestus, M., and Baayen, R. (2005). Lexical frequency and acoustic reduction in spoken Dutch. The Journal of the Acoustical Society of America, 118, 25-61. pluymaekersetal05.pdf pdf Alan Bell, Jason Brenier, Michelle Gregory, Cynthia Girand, and Dan Jurafsky. (2009) Predictability Effects on Durations of Content and Function Words in Conversational English. Journal of Memory and Language 60:1, 92-111. belletal09.pdf pdf Aylett, M. and Turk, A. (2004). The smooth signal redundancy hypothesis: A functional explanation for relationships between redundancy, prosodic prominence, and duration in spontaneous speech. Language and Speech, 47(1), 31-56. aylettturk04.pdf pdf Gahl, S., Garnsey, S. M., Fisher, C., & Matzen, L. (2006). "That sounds unlikely": Syntactic probabilities affect pronunciation. Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 1334-1339). Van Son, R., and Pols, L. (2003). How efficient is speech? Proceedings of the Institute of Phonetic Sciences, 25, 171-184. vansonpols03.pdf pdf Aylett, M.P. and Turk, A. (2006) Language redundancy predicts syllabic duration and the spectral characteristics of vocalic syllable nuclei. The Journal of the Acoustical Society of America 119, 30-48. aylettturk06.pdf pdf van Son, R. and van Santen, J. (2005) Duration and spectral balance of intervocalic consonants: A case for efficient communication. Speech Communication 47(1), 100-123. vansonvansanten05.pdf pdf Shriberg, E., & Stolcke, A. (1996). Word predictability after hesitations: A corpus-based study. In Proceedings of ICSLP '96. Cook, S. W., Jaeger, T. F., & Tanenhaus, M. K. (2009). Producing less preferred structures: More gestures, less Fluency. In Proceedings of the 31st conference of the Cognitive Science Society. Vancouver, BC. Clark, H. H., & Fox Tree, J. E. (2002). Using "uh" and "um" in spontaneous speech. Cognition, 84, 73-111. Frank, A., & Jaeger, T.F. (2008, July). Speaking rationally: Uniform information density as an optimal strategy for language production. In The 30th annual meeting of the Cognitive Science Society (CogSci08) (p. 933-938). Washington, D.C. Wasow, T., Jaeger, T.F., & Orr, D. (in press). Lexical variation in relativizer frequency. In H. Wiese & H. Simon (Eds.), Proceedings of the workshop on expecting the unexpected: Exceptions in grammar at the 27th annual meeting of the German Linguistic Association. Berlin and New York: Mouton de Gruyter. Brown, P., & Dell, G.S. (1987). Adapting production to comprehension: The explicit mention of instruments. Cognitive Psychology, 19 (4), 441-472. Gomez Gallo, C., Jaeger, T. F., & Smyth, R. (2008, July). Incremental syntactic planning across clauses. In The 30th annual meeting of the Cognitive Science Society (CogSci08) (p. 845-850). Washington, D.C. Levy, R., & Jaeger, T.F. (2007). Speakers optimize information density through syntactic reduction. In B. Schlokopf, J. Platt, & T. Homan (Eds.), Advances in neural information processing systems (NIPS) 19 (p. 849-856). Cambridge, MA: MIT Press. Smith, N., & Levy, R. (2008, July). Optimal processing times in reading: A formal model and empirical investigation. In The 30th annual meeting of the Cognitive Science Society (CogSci08). Washington, D.C.. Tily & Piantadosi (2009). Refer efficiently: Use less informative expressions for more predictable meanings. Proceedings of the Workshop on Production of Referring Expressions, Cogsci 2009. Dell, G. S., Chang, F., & Grin, Z. M. (1999). Connectionist models of language production: Lexical access and grammatical encoding. Cognitive Science: A Multidisciplinary Journal, 23 (4), 517-542. Chang, F., Dell, G. S., & Bock, J. K. (2006). Becoming syntactic. Psychological Review, 113 (2), 234-272. focusing on discussion of competition accounts, have another look at: Cook, S. W., Jaeger, T. F., & Tanenhaus, M. K. (2009). Producing less preferred structures: More gestures, less Fluency. In Proceedings of the 31st conference of the Cognitive Science Society. Vancouver, BC. Zipf 1935 (73-81, 109-121) and Zipf 1949 (98-108) on phonological change Zipf35-49_sound.pdf pdf Schuchardt, H. (1885) On sound laws: Against Neogrammarians. Translated by T. Vennemann and T.H. Wilbur. schuchardt1885.pdf pdf Bates, E. and MacWhinney, B. (1982) Milin, P., Kuperman, V., Kostic, A. & Baayen, R.H. Paradigms bit by bit: an information- theoretic approach to the processing of inflection and derivation. In press in Blevins, James P. and Juliette Blevins (eds.), Analogy in Grammar: Form and Acquisition. Oxford: Oxford University Press.
Snider & Jaeger
More than a Curious Phenomenon? Constant Entropy Rate
Probability and Information in Online Language Production
Computational Accounts and Mechanisms
Language Change: The Link between Processing and Grammar
The End Topics
Computational Approaches to Production
Background in probability theory and information theory Computational Models of Priming, Implicit Learning, Adaptation
Priming and Implicit Learning