PSYCH 227/LING 247: Seminar in Psycholinguistics: Models of Human and Machine Speech and Language Processing

PSYCH 227 / LINGUIST 247: Seminar in Psycholinguistics: Models of Human and Machine Speech and Language Processing

Winter 2007

COURSE INFORMATION

Instructor

Dan Jurafsky, jurafsky@stanford.edu
Office: Margaret Jacks Hall (bld 460) 113
Office Hours: TBA

Time
Tuesdays 3:45-6:30pm

Location
50-51P

Description
This seminar is designed to focus on the relationship between computational models of language processing from psychology and from engineering. Our goal will mainly be to look for interesting ways to enrich the cognitive modeling literature with insights from recent engineering models of language computation.

Required Work

60%: Presentation of two papers
40%: Participation in discussion

SCHEDULE

Wk

Date

Who

Topic and Readings

1
Jan 9
Me
Planning meeting; choosing course topics and direction.

2
Jan 16
(respectively:)

Anubha
Uriel
Jan (slides pdf)
David

Issues in Statistical Parsing in Humans and Machines

Tabor, W., Galantucci, B., & Richardson, D. (2004). Effects of Merely Local Syntactic Coherence on Sentence Processing. Journal of Memory and Language 50(4), 355-370

Gibson, E. (2006). The interaction of top-down and bottom-up statistics in the resolution of syntactic category ambiguity. Journal of Memory and Language, 54, 363-388.

Hale, John. 2001. A Probabilistic Earley Parser as a Psycholinguistic Model. In Proceedings of the Second Meeting of the North American Chapter of the Asssociation for Computational Linguistics.

Dan Klein and Chris Manning. 2003. Accurate Unlexicalized Parsing ACL-03, 2003.

3
Jan 23
(respectively:)

Yuan
Kem PDF
Anubha
Hal PDF

Constant Entropy Rate

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.
Genzel, D. and Charniak, E. (2002). Entropy rate constancy in text. In Proceedings of ACL-02.
Keller, F. (2004). The entropy rate principle as a predictor of processing effort: An evaluation against eye-tracking data. In In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Barcelona, pp. 317-324.
Roger Levy and T. Florian Jaeger. 2006. Speakers optimize information density through syntactic reduction. Pre-proceedings version to appear in Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems.

4
Jan 30
(respectively:)

Neal
Nate
David
Aaron

Alignment, Mimicry, Chameleons, and Speed Dating

Pickering, M. J. & Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27, 169-226. (noting especially this rebuttal: Brennan, S. E. & Metzing, C. A. (2004). "Two steps forward, one step back: Partner-specific effects in a psychology of dialogue." Behavioral and Brain Sciences. 1 page reply to above.)
Bailenson, J.N., Yee, N., Patel, K., & Beall, A.C. (2007, in press). Detecting Digital Chameleons. Computers in Human Behavior.
Anmol Madan, Ron Caneel, Alex Pentland. 2005. Voices of Attraction. AugCog Symposium of HCI 2005
Bailenson, J. N. & Yee, N. (2005). Digital Chameleons: Automatic assimilation of nonverbal gestures in immersive virtual environments. Psychological Science, 16, 814-819. (see VIDEO)

Some optional extra papers; the first one is computational.

Jared Curhan, Alex Pentland, Ron Caneel, Nathan Eagle, Martin Martin. 2005. Thin Slices of Negotation. Annual Meeting of the Academy of Management.)
Tanya L. Chartrand and John A. Bargh. 1999. The Chameleon Effect: The Perception-Behavior Link and Social Interaction. Journal of Personality and Social Psychology 1999, Vol. 76, No. 6, 893-910

5
Feb 6
Sharon (Slides)

Half-day: Tutorial and recent experiments on Bayesian Models (3:45-5:15 only)

J. Tenenbaum and F. Xu. Word learning as Bayesian inference. In Proc. 22nd Ann. Conf. Cognitive Science Society, 2000.
J. Tenenbaum and F. Xu. 2005. Word learning as Bayesian inference: Evidence from Preschoolers. Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society.
LouAnn Gerken. 2006. Decisions, decisions: infant language learning when multiple generalizations are possible. Cognition 98.

6
Feb 13

Jeremy
Yuan
Kem PDF
Jan (slides pdf)

Development of Segmentation

Thiessen, E. D., & Saffran, J. R. (2004). Spectral tilt as a cue to word segmentation in infancy and adulthood. Perception & Psychophysics, 66, 779-791
Kuhl, P. K., Tsao. F.-M., & Liu, H.-M. (2003). Foreign-language experience in infancy: Effects of short-term exposure and social interaction on phonetic learning. Proceedings of the National Academy of Sciences, 100, 9096-9101
Gambell, T. & Yang, C. 2005. Mechanisms and Constraints in Word Segmentation. Unpublished manuscript.
Christiansen, M. H., Allen, J., & Seidenberg, M. S. (1998). Learning to segment speech using multiple cues: A connectionist model. Language and Cognitive Processes, 13(2-3), 221-268.

7
Feb 20

Inbal
Daniel
Casey
Casey

Early parsing mechanisms and higher-order units in infants

Thiessen, E.D., Hill, E.A., Saffran, J.R. (2005) Infant-directed speech facilitates word segmentation. Infancy, 7, 53-71.
Toro JM, Sinnett S, and Soto-Faraco S. (2005). Speech segmentation by statistical learning depends on attention. Cognition 97(2):B25-34
Graf Estes, K., Evans, J.L., Alibali, M.W., and Saffran, J.R. (2006) Can infants map meaning to newly segmented words? Statistical segmentation and word learning. In press, Psychological Science
Chen Yu and Linda B. Smith. In press. Rapid Word Learning under Uncertainty via Cross-Situational Statistics , Psychological Science, in press.

8
Feb 27

Ani
Sharon

Computational Models of Lexical Access

Norris, D. (in press) The Bayesian Reader: Explaining word recognition as an optimal Bayesian decision process. Psychological Review .
Vitevitch, M.S. and Luce, P.A. (1999). Probabilistic phonotactics and neighborhood activation in spoken word recognition. Journal of Memory & Language, 40, 374-408.

9
Mar 6

Neal
Uriel
Jeremy
Jeremy
Jeremy
Jeremy

Two topics: Word Similarity and Marcus article

Mohammad, S. and Hirst, G. (2005). Distributional measures as proxies for semantic relatedness.
Landauer, T. K. and Dumais, S. T. (1997). A solution to Plato's problem: The Latent Semantic Analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211-240.
Marcus, G. F., Vijayan, S., Bandi Rao, S., and Vishton, P. M. (1999). Rule-learning in seven-month-old infants. Science, 283, 77-80.
Some responses and counter-responses
More responses and counter-responses
Optional: the Elman simulation

10
Mar 13

Nate
Daniel
Aaron

Time

Moens, Marc and Mark Steedman. 1988. Temporal Ontology and Temporal Reference. Computational Linguistics 14:2, 15-28.
Gennari, Silvia P. 2004. Temporal References and Temporal Relations in Sentence Comprehension. Journal of Experiment Psychology: Learning, Memory, and Cognition 30:4 877-890.
Mani, I. and Schiffman, B. To appear. Temporally Anchoring and Ordering Events in News (DRAFT)" To appear in James Pustejovsky and Robert Gaizauskas (eds.) Event Recognition in Natural Language. John Benjamins.

COURSE INFORMATION
Instructor	Dan Jurafsky, jurafsky@stanford.edu Office: Margaret Jacks Hall (bld 460) 113 Office Hours: TBA
Time	Tuesdays 3:45-6:30pm
Location	50-51P
Description	This seminar is designed to focus on the relationship between computational models of language processing from psychology and from engineering. Our goal will mainly be to look for interesting ways to enrich the cognitive modeling literature with insights from recent engineering models of language computation.
Required Work	60%: Presentation of two papers 40%: Participation in discussion

	SCHEDULE
Wk	Date	Who	Topic and Readings
1	Jan 9	Me	Planning meeting; choosing course topics and direction.
2	Jan 16	(respectively:) Anubha Uriel Jan (slides pdf) David	Issues in Statistical Parsing in Humans and Machines Tabor, W., Galantucci, B., & Richardson, D. (2004). Effects of Merely Local Syntactic Coherence on Sentence Processing. Journal of Memory and Language 50(4), 355-370 Gibson, E. (2006). The interaction of top-down and bottom-up statistics in the resolution of syntactic category ambiguity. Journal of Memory and Language, 54, 363-388. Hale, John. 2001. A Probabilistic Earley Parser as a Psycholinguistic Model. In Proceedings of the Second Meeting of the North American Chapter of the Asssociation for Computational Linguistics. Dan Klein and Chris Manning. 2003. Accurate Unlexicalized Parsing ACL-03, 2003.
3	Jan 23	(respectively:) Yuan Kem PDF Anubha Hal PDF	Constant Entropy Rate 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. Genzel, D. and Charniak, E. (2002). Entropy rate constancy in text. In Proceedings of ACL-02. Keller, F. (2004). The entropy rate principle as a predictor of processing effort: An evaluation against eye-tracking data. In In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Barcelona, pp. 317-324. Roger Levy and T. Florian Jaeger. 2006. Speakers optimize information density through syntactic reduction. Pre-proceedings version to appear in Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems.
4	Jan 30	(respectively:) Neal Nate David Aaron	Alignment, Mimicry, Chameleons, and Speed Dating Pickering, M. J. & Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27, 169-226. (noting especially this rebuttal: Brennan, S. E. & Metzing, C. A. (2004). "Two steps forward, one step back: Partner-specific effects in a psychology of dialogue." Behavioral and Brain Sciences. 1 page reply to above.) Bailenson, J.N., Yee, N., Patel, K., & Beall, A.C. (2007, in press). Detecting Digital Chameleons. Computers in Human Behavior. Anmol Madan, Ron Caneel, Alex Pentland. 2005. Voices of Attraction. AugCog Symposium of HCI 2005 Bailenson, J. N. & Yee, N. (2005). Digital Chameleons: Automatic assimilation of nonverbal gestures in immersive virtual environments. Psychological Science, 16, 814-819. (see VIDEO) Some optional extra papers; the first one is computational. Jared Curhan, Alex Pentland, Ron Caneel, Nathan Eagle, Martin Martin. 2005. Thin Slices of Negotation. Annual Meeting of the Academy of Management.) Tanya L. Chartrand and John A. Bargh. 1999. The Chameleon Effect: The Perception-Behavior Link and Social Interaction. Journal of Personality and Social Psychology 1999, Vol. 76, No. 6, 893-910
5	Feb 6	Sharon (Slides)	Half-day: Tutorial and recent experiments on Bayesian Models (3:45-5:15 only) J. Tenenbaum and F. Xu. Word learning as Bayesian inference. In Proc. 22nd Ann. Conf. Cognitive Science Society, 2000. J. Tenenbaum and F. Xu. 2005. Word learning as Bayesian inference: Evidence from Preschoolers. Proceedings of the Twenty-Seventh Annual Conference of the Cognitive Science Society. LouAnn Gerken. 2006. Decisions, decisions: infant language learning when multiple generalizations are possible. Cognition 98.
6	Feb 13	Jeremy Yuan Kem PDF Jan (slides pdf)	Development of Segmentation Thiessen, E. D., & Saffran, J. R. (2004). Spectral tilt as a cue to word segmentation in infancy and adulthood. Perception & Psychophysics, 66, 779-791 Kuhl, P. K., Tsao. F.-M., & Liu, H.-M. (2003). Foreign-language experience in infancy: Effects of short-term exposure and social interaction on phonetic learning. Proceedings of the National Academy of Sciences, 100, 9096-9101 Gambell, T. & Yang, C. 2005. Mechanisms and Constraints in Word Segmentation. Unpublished manuscript. Christiansen, M. H., Allen, J., & Seidenberg, M. S. (1998). Learning to segment speech using multiple cues: A connectionist model. Language and Cognitive Processes, 13(2-3), 221-268.
7	Feb 20	Inbal Daniel Casey Casey	Early parsing mechanisms and higher-order units in infants Thiessen, E.D., Hill, E.A., Saffran, J.R. (2005) Infant-directed speech facilitates word segmentation. Infancy, 7, 53-71. Toro JM, Sinnett S, and Soto-Faraco S. (2005). Speech segmentation by statistical learning depends on attention. Cognition 97(2):B25-34 Graf Estes, K., Evans, J.L., Alibali, M.W., and Saffran, J.R. (2006) Can infants map meaning to newly segmented words? Statistical segmentation and word learning. In press, Psychological Science Chen Yu and Linda B. Smith. In press. Rapid Word Learning under Uncertainty via Cross-Situational Statistics , Psychological Science, in press.
8	Feb 27	Ani Sharon	Computational Models of Lexical Access Norris, D. (in press) The Bayesian Reader: Explaining word recognition as an optimal Bayesian decision process. Psychological Review . Vitevitch, M.S. and Luce, P.A. (1999). Probabilistic phonotactics and neighborhood activation in spoken word recognition. Journal of Memory & Language, 40, 374-408.
9	Mar 6	Neal Uriel Jeremy Jeremy Jeremy Jeremy	Two topics: Word Similarity and Marcus article Mohammad, S. and Hirst, G. (2005). Distributional measures as proxies for semantic relatedness. Landauer, T. K. and Dumais, S. T. (1997). A solution to Plato's problem: The Latent Semantic Analysis theory of acquisition, induction, and representation of knowledge. Psychological Review, 104, 211-240. Marcus, G. F., Vijayan, S., Bandi Rao, S., and Vishton, P. M. (1999). Rule-learning in seven-month-old infants. Science, 283, 77-80. Some responses and counter-responses More responses and counter-responses Optional: the Elman simulation
10	Mar 13	Nate Daniel Aaron	Time Moens, Marc and Mark Steedman. 1988. Temporal Ontology and Temporal Reference. Computational Linguistics 14:2, 15-28. Gennari, Silvia P. 2004. Temporal References and Temporal Relations in Sentence Comprehension. Journal of Experiment Psychology: Learning, Memory, and Cognition 30:4 877-890. Mani, I. and Schiffman, B. To appear. Temporally Anchoring and Ordering Events in News (DRAFT)" To appear in James Pustejovsky and Robert Gaizauskas (eds.) Event Recognition in Natural Language. John Benjamins.