Lisa S. Pearl

• Director of CoLaLab
  
• Research Topics
  
• Publications
  
• Selected Presentations & Posters
  
• Other Useful Things
  

	Research Topics
	Language Acquisition
	Models of Acquirability
	Linguistic Cues to Information
	Foundations
	Theoretical Linguistics
	Natural Language Processing

	Pearl, L. & Forsythe, H. (under review, updated 2/1/24). Inaccurate representations, inaccurate deployment, or both? Using computational cognitive modeling to investigate the development of pronoun interpretation in Spanish. Language. [lingbuzz]. Code available at github.
	Pearl, L. (under review, updated 12/19/23). Minimalism for language acquisition. In Kleanthes Grohmann & Evelina Leivada (eds.), The Cambridge Handbook of Minimalism and Its Applications. [lingbuzz]
	Attali, N., Scontras, G., Pearl, L., & Wulff, S. (under review, updated 5/26/23). Using world knowledge to interpret quantifier-scope ambiguity. Language.
	Dickson, N., Futrell, R., & Pearl, L. (in press 1/25/24). I Forgot but It’s Okay: Learning about Island Constraints under Child-Like Memory Constraints. In Proceedings of the 48th annual Boston University Conference on Language Development. [lingbuzz] [code]
	Pearl, L. 2023. Computational cognitive modeling for syntactic acquisition: Approaches that integrate information from multiple places. Journal of Child Language, 50(6), 1353-1373. https://doi.org/10.1017/S0305000923000247 [lingbuzz] [journal version]
	Pearl, L. 2023. Modeling syntactic acquisition. In J. Sprouse (ed.), Oxford Handbook of Experimental Syntax, 209-270. [lingbuzz] Includes future directions and annotated bibliography.
	Pearl, L. & Bates, A. 2022. A new way to identify if variation in children's input could be developmentally meaningful: Using computational cognitive modeling to assess input across socio-economic status for syntactic islands. Journal of Child Language, 1-34. doi:10.1017/S0305000922000514. [lingbuzz].
	Attali, N., Pearl, L., & Scontras, G. 2022. Corpus evidence for the role of world knowledge in ambiguity reduction: Using high positive expectations to inform quantifier scope. In Proceedings of Experiments in Linguistic Meaning, 2.
	Dickson, N., Pearl, L., & Futrell, R. 2022. Learning constraints on wh-dependencies by learning how to efficiently represent wh-dependencies: A developmental modeling investigation with Fragment Grammars. In Proceedings of the Society for Computation in Linguistics, 5, Article 22. https://doi.org/10.7275/7fd4-fw49. [lingbuzz].
	Pearl, L. 2021. Poverty of the Stimulus Without Tears. Language Learning and Development. doi: 10.1080/15475441.2021.1981908. [lingbuzz].
	Scontras, G. & Pearl, L. 2021. When pragmatics matters more for truth-value judgments: An investigation of quantifier scope ambiguity. Glossa: A Journal of General Linguistics, 6(1), doi: https://doi.org/10.16995/glossa.5724. [lingbuzz].
	Nguyen, E. & Pearl, L. 2021. The link between lexical semantic features and children's comprehension of English be-passives. Language Acquisition, 28(4), 433-450. [online] [lingbuzz].
	Pearl, L. 2021. How statistical learning can play well with Universal Grammar. In Nicholas Allott, Terje Lohndal & Georges Rey (eds.), Wiley-Blackwell Companion to Chomsky, Wiley-Blackwell, 267-286. [lingbuzz]
	Attali, N., Scontras, G. & Pearl, L. 2021. Pragmatic factors can explain variation in interpretation preferences for quantifier-negation utterances: A computational approach. In Proceedings of the 43rd annual meeting of the Cognitive Science Society, Vienna, Austria: Cognitive Science Society.
	Attali, N., Scontras, G. & Pearl, L. 2021. Every quantifier isn't the same: Informativity matters for ambiguity resolution in quantifier-negation sentences. In Proceedings of the Society for Computation in Linguistics, 4, 394-395.
	Pearl, L. & Sprouse, J. 2021. The acquisition of linking theories: A Tolerance and Sufficiency Principle approach to learning UTAH and rUTAH. Language Acquisition, doi: 10.1080/10489223.2021.1888295. [lingbuzz]. Code available at github (derived-tolp subdirectory).
	Pearl, L. 2021. Theory and predictions for the development of morphology and syntax: A Universal Grammar + statistics approach. Special issue of the Journal of Child Language, 48(5), 907-936. doi: 10.1017/S0305000920000665. [lingbuzz]
	Vogler, N. & Pearl, L. 2020. Using linguistically-defined specific details to detect deception across domains. Natural Language Engineering, 26(3), 349-373.
	Pearl, L. 2020. Leveraging monolingual developmental techniques to better understand heritage languages. Bilingualism: Language & Cognition, 23(1), 39-40. https://doi.org/10.1017/S1366728919000361. [link to official version] [lingbuzz]
	Pearl, L. & Sprouse, J. 2019. Comparing solutions to the linking problem using an integrated quantitative framework of language acquisition. Language, 95(4), 583-611. [lingbuzz]. Code available at github.
	Forsythe, H. & Pearl, L. 2019. Immature representation or immature deployment? Modeling child pronoun resolution. In Proceedings of the Society for Computation in Linguistics, 3, article 59. [scholarworks] [lingbuzz]
	Nyguen, E. & Pearl, L. 2019. Using Developmental Modeling to Specify Learning and Representation of the Passive in English Children. In Proceedings of the 43rd annual Boston University Conference on Language Development, Megan M. Brown and Brady Dailey (eds), Somerville, MA: Cascadilla Press, 469-482. [lingbuzz]
	Bates, A. & Pearl, L. 2019. *What do you think that happens? A quantitative and cognitive modeling analysis of linguistic evidence across socioeconomic status for learning syntactic islands. In Proceedings of the 43rd annual Boston University Conference on Language Development, Megan M. Brown and Brady Dailey (eds), Somerville, MA: Cascadilla Press, 42-56. [lingbuzz]
	Pearl, L. 2019. Fusion is great, and interpretable fusion could be exciting for theory generation. Perspectives section of Language, 95(1), e109-e114. [lingbuzz].
	Bates, A., Pearl, L., and Braunwald, S. 2018. I can believe it: Quantitative evidence for closed-class category knowledge in an English-speaking 20- to 24-month-old child. In Proceedings of the Berkeley Linguistics Society, K. Garvin, N. Hermalin, M. Lapierre, Y. Melguy, T. Scott, & E. Wilbanks (eds), 1-16. [lingbuzz]
	Bar-Sever G., Lee, R., Scontras, G., and Pearl, L. 2018. Little lexical learners: Quantitatively assessing the development of adjective ordering preferences. In Bertolini, A. & Kaplan, M. (eds), BUCLD 42 Proceedings, Somerville, MA: Cascadilla Press, 58-71. [lingbuzz] [data (zip)]
	Savinelli, K., Scontras, G., and Pearl, L. 2018. Exactly two things to learn from modeling scope ambiguity resolution: Developmental continuity and numeral semantics. In Proceedings of the 8th Workshop on Cognitive Modeling and Computational Linguistics, Salt Lake City, UT.
	Pearl, L. & Phillips, L. 2018. Evaluating language acquisition models: A utility-based look at Bayesian segmentation. In A. Villavicencio & T. Poibeau (eds), Language, Cognition and Computational Models, Cambridge University Press, 185-224.
	Nguyen, E. and Pearl, L. 2018. Do You Really Mean It? Linking Lexical Semantic Profiles and the Age of Acquisition for the English Passive. In Proceedings of the 35th West Coast Conference on Formal Linguistics, Wm. G. Bennett, Lindsay Hracs, and Dennis Ryan Storoshenko (eds), Somerville, MA: Cascadilla Proceedings. 288-295. [lingbuzz]
	Pearl, L., Ho, T., & Detrano, Z. 2017. An argument from acquisition: Comparing English metrical stress representations by how learnable they are from child-directed speech. Language Acquisition, 24, 307-342. [lingbuzz] [data: xls][code: zip and github]
	Savinelli, K., Scontras, G., and Pearl, L. 2017. Modeling scope ambiguity resolution as pragmatic inference: Formalizing differences in child and adult behavior. In Proceedings of the 39th annual meeting of the Cognitive Science Society, London, UK: Cognitive Science Society, 3064-3069.
	Pearl, L., Scontras, G., & Singh, S. 2017. Large-scale sophisticated linguistic monitoring. A Decadal Survey of the Social and Behavioral Sciences for National Security, Division of Behavioral and Social Sciences and Education (DBASSE) of the National Academies.
	Pearl, L. 2017. Evaluation, use, and refinement of knowledge representations through acquisition modeling. [lingbuzz]. Language Acquisition, 24, 126-147.
	Bar-Sever, G. & Pearl, L. 2016. Syntactic Categories Derived from Frequent Frames Benefit Early Language Processing in English and ASL. Proceedings of the 40th annual Boston University Conference on Language Development (ed. Jennifer Scott and Deb Waughtal), Somerville, MA: Cascadilla Press, 32-46. pre-print copy
	Pearl, L., & Mis, B. 2016. The role of indirect positive evidence in syntactic acquisition: A look at anaphoric one. Supplementary material pdf. Language, 92(1), 1-30. [lingbuzz]
	Pearl, L., Lu, K., & Haghighi, A. 2016. The Character in the Letter: Epistolary Attribution in Samuel Richardson's Clarissa. Digital Scholarship in the Humanities, 32 (2), 355-376. doi: 10.1093/llc/fqw007. (DSH final) [Clarissa Letters Dataset: zip]
	Pearl, L. & Goldwater, S. 2016. Statistical Learning, Inductive Bias, and Bayesian Inference in Language Acquisition. In J. Lidz, W. Snyder, & C. Pater (eds), The Oxford Handbook of Developmental Linguistics, 664-695.
	Phillips, L. & Pearl, L. 2015. (Manuscript. Last updated 5/13/15). Evaluating language acquisition strategies: A cross-linguistic look at early segmentation. [cross-ling data: github]
	Pearl, L. & Braunwald, S. 2015. Review of Language in Mind: An Introduction to Psycholinguistics by Julie Sedivy. Teaching Linguistics subsection of Language, 91(4), e181-183.
	Phillips, L. & Pearl, L. 2015. The utility of cognitive plausibility in language acquisition modeling: Evidence from word segmentation. Cognitive Science, 39(8), 1824-1854. doi: 10.1111/cogs.12217. [Code & corpora: github]
	Pearl, L., & Sprouse, J. 2015. Computational modeling for language acquisition: A tutorial with syntactic islands. Journal of Speech, Language, and Hearing Research, 58, 740-753. doi: 10.1044/2015_JSLHR-L-14-0362. [lingbuzz] [JSLHR]
	Phillips, L. & Pearl, L. 2015. Utility-based evaluation metrics for models of language acquisition: A look at speech segmentation. Workshop on Cognitive Modeling and Computational Linguistics 2015, NAACL.
	Pearl, L. & Enverga, I. 2015. Can you read my mindprint? Automatically identifying mental states from language text using deeper linguistic features. Interaction Studies, 15(3) 359-387.
	Pearl, L., Ho, T., & Detrano, Z. 2014. More learnable than thou? Testing metrical phonology representations with child-directed speech. Proceedings of the Berkeley Linguistics Society, 398-422. [lingbuzz][data: xls][code: zip and github]
	Pearl, L. 2014. Evaluating learning strategy components: Being fair. Language, 90(3), e107-e114. [lingbuzz] [Language]
	Phillips, L. & Pearl, L. 2014. Bayesian inference as a viable cross-linguistic word segmentation strategy: It's all about what's useful. Proceedings of the 36th Annual Conference of the Cognitive Science Society, Quebec City, CA: Cognitive Science Society, 2775-2780.
	Phillips, L. & Pearl, L. 2014. Bayesian inference as a cross-linguistic word segmentation strategy: Always learning useful things. Proceedings of the Computational and Cognitive Models of Language Acquisition and Language Processing Workshop, EACL, Gothenberg, Sweden, 9-13.
	Pearl, L. & Sprouse, J. 2013. Computational Models of Acquisition for Islands, In J. Sprouse & N. Hornstein (eds), Experimental Syntax and Islands Effects. Cambridge University Press, 109-131.
	Pearl, L. & Steyvers, M. 2013. "C'mon - You Should Read This": Automatic Identification of Tone from Language Text. International Journal of Computational Linguistics, 4(1), 12-30.
	Pearl, L., & Mis, B. 2013. Induction problems, indirect positive evidence, and Universal Grammar: Anaphoric one revisited. University of California, Irvine. [lingbuzz]
	Pearl, L. & Lidz, J. 2013. Parameters in Language Acquisition. In C. Boeckx & K. Grohmann (eds), The Cambridge Handbook of Biolinguistics, Cambridge, UK: Cambridge University Press, 129-159.
	Pearl, L. & Sprouse, J. 2013. Syntactic islands and learning biases: Combining experimental syntax and computational modeling to investigate the language acquisition problem. Language Acquisition, 20, 23-68. DOI 10.1080/10489223.2012.738742. [lingbuzz] [code @ github]
	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.
	Pearl, L. & Steyvers, M. 2012. Detecting Authorship Deception: A Supervised Machine Learning Approach Using Author Writeprints, Literary and Linguistic Computing, 27(2), 183-196. DOI 10.1093/llc/fqs003.
	Caponigro, I., Pearl, L., Brooks, N., and Barner, D. 2012. Acquiring the meaning of free relative clauses and plural definite descriptions, Journal of Semantics, 29, 261-293. DOI 10.1093/jos/ffr014.
	Pearl, L., Goldwater, S., & Steyvers, M. 2011. Online Learning Mechanisms for Bayesian Models of Word Segmentation, Research on Language and Computation, special issue on computational models of language acquisition, 8(2), 107-132. DOI 10.1007/s11168-011-9074-5.
	Caponigro, I., Pearl, L., Brooks, N., & Barner, D. 2011. On the acquisition of maximality in free relative clauses and plural definite descriptions, In Nan Li and David Lutz (eds.), Proceedings from Semantic and Linguistic Theory, 20, Vancouver, British Columbia: SALT, 508-524.
	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. 2011. When unbiased probabilistic learning is not enough: Acquiring a parametric system of metrical phonology. Language Acquisition, 18(2), 87-120.
	Pearl, L. 2010. Using computational modeling in language acquisition research, In E. Blom & S. Unsworth (eds). Experimental Methods in Language Acquisition Research, John Benjamins, 163-184.
	Pearl, L. & Steyvers, M. 2010. Identifying Emotions, Intentions, & Attitudes in Text Using a Game with a Purpose. Proceedings of NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. Los Angeles, CA: NAACL.
	Pearl, L., Goldwater, S., & Steyvers, M. 2010. How Ideal Are We? Incorporating Human Limitations into Bayesian Models of Word Segmentation, In In K. Franich, K. Iserman, and L. Keil (eds), Proceedings of the 34th annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press, 315-326.
	Pearl, L. 2009 Ms. Acquiring parametric linguistic systems from natural language data: What selective learning biases can do, Manuscript, University of California, Irvine.
	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. (available through the Cascadilla Proceedings Project Website)
	Pearl, L. & Lidz, J. 2009. When domain general learning fails and when it succeeds: Identifying the contribution of domain specificity, Language Learning and Development, 5(4), 235-265.
	Caponigro, I. & Pearl, L. 2009. The nominal nature of Where, When, and How: Evidence from Free Relatives, Linguistic Inquiry, 40.1, 155-164.
	Caponigro, I. & Pearl, L. 2008. Silent Prepositions: Evidence from Free Relatives, In Anna Asbury, Jakub Dotlaèil, Berit Gehrke, and Rick Nouwen (eds), The Syntax and Semantics of Spatial P, Amsterdam: Benjamins.
	Pearl, L. 2008. Putting the Emphasis on Unambiguous: The Feasibility of Data Filtering for Learning English Metrical Phonology, BUCLD 32: Proceedings of the 32nd annual Boston University Conference on Child Language Development, Chan, H., Jacob, H., and Kapia, E (eds.), Somerville, MA: Cascadilla Press, 390-401.
	Lidz, J. & Pearl, L. 2007. Language Learning through Selection. review of Charles Yang's The Infinite Gift: How Children Learn and Unlearn the Languages of the World, Science, 315, 332.
	Pearl, L. & Weinberg, A. 2007. Input Filtering in Syntactic Acquisition: Answers from Language Change Modeling, Language Learning and Development, 3(1), 43-72.
	Pearl, L. 2005. The Input to Syntactic Acquisition: Solutions from Language Change Modeling, Proceedings of Second Workshop on Psychocomputational Models of Human Language Acquisition, Ann Arbor, Michigan, 1-9.
	Pearl, L. 2005. Addressing Acquisition from Language Change: A Modeling Perspective, University of Pennsylvania Working Papers in Linguistics, 11.1.
	Dorr, B., Pearl, L., Hwa, R., & Habash, N. 2003. "DUSTer: A Method for Unraveling Cross-Language Divergences for Statistical Word-Level Alignment", Lecture Notes in Computer Science, Springer-Verlag, 31-43.
	Dorr, B., Pearl, L., Hwa, R., & Habash, N. 2002. "Improved Word Level Alignment: Injecting Knowledge about MT Divergences", Technical Report ACL-2002-P0364, Language and Media Processing Laboratory, University of Maryland, College Park.
	Green, R., Dorr, B., & Pearl, L. 2001. Mapping WordNet Senses to a Lexical Database of Verbs, Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics, Toulouse, France.
	Green, R., Pearl, L., Dorr, B., & Resnik, P. 2001. Lexical Resource Integration Across the Syntax-Semantics Interface, Technical Report LAMP-TR-069/CS-TR-4231/UMIACS-TR-2001-19/CS-TR-4231, University of Maryland, College Park.

Doctoral Dissertation, University of Maryland:
Necessary Bias in Natural Language Learning

Necessary Bias in Natural Language Learning (all)     Abstract     Opening Information     Ch.1: A Theory of the Language Learning Mechanism     Ch.2: Bayesian Updating in a Linguistic Framework     Ch.3: The Case of Anaphoric One     Ch.4: The Case of Old English Word Order     Ch.5, Ch.6 & Appendix: The Case of English Metrical          Phonology & Learning By Filtering     Bibilography

Selected Presentations & Posters

	2024     "Computational cognitive modeling: How to investigate child language acquisition using math.", Linguistics Student Association, California State University, Fullerton. presentation (pdf) (youtube video playlist)
	2024     "How to succeed at syntactic island acquisition without really trying: Learning the right bulding blocks", Pomona Acquisition Workshop, Pomona College. presentation (pdf)
	2023     "How to succeed at syntactic island acquisition without really trying: Learning about local structure", Workshop on Locality in Theory, Processing, and Acquisition, Penn Syntax Lab, University of Pennsylvania. presentation (pdf) (youtube video playlist)
	2022     "Adventures in computational modeling for syntactic acquisition: A look at syntactic islands", Linguistics Colloquium, University of Arizona and Language Evolution, Acquisition, and Processing Workshop (LEAP), Department of Linguistics, University of Chicago. presentation (pdf) (youtube: intro, part 1, part 2, part 3, part 4, part 5, part 6, part 7, takeaway)
	2021     "A new way to identify if variation in children’s input is developmentally meaningful: A look at syntactic knowledge across socio-economic status", EyeLands Lab, Norwegian University of Science and Technology. presentation (pdf) (youtube: intro, part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part 9, takeaway)
	2021     "How children are and aren't like adults when interpreting pronouns: A developmental modeling investigation", Linguistics Colloquium, UCLA 2021 and Rutgers 2021. presentation (pdf) (youtube: intro 1, intro 2, intro 3, part 1, part 2, part 3, part 4, part 5, part 6, takeaway)
	2021     "How children are and aren't like adults when it comes to interpreting pronouns: A developmental modeling investigation", Computational Linguistics and Information Processing Colloquium, University of Maryland, College Park. presentation (pdf) (youtube: intro 1, intro 2, intro 3, part 1, part 2, part 3, part 4, part 5, part 6, takeaway)
	2021     "How math helps us better understand language", Linguistics Studies Lecture Series, College of Charleston. presentation (pdf) (youtube: intro, part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part 9 (takeaway))
	2020     "A new way to find developmentally-meaningful variation in children’s input: A look at syntactic knowledge across socio-economic status", Linguistics Colloquium, University of Maryland, College Park. presentation (pdf) (youtube: intro: part 1, intro: part 2, intro: part 3, part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part 9, part 10 (takeaway))
	2020     "A new way to find developmentally-meaningful variation in children’s input: A look at syntactic knowledge across socio-economic status", ForMA Colloquium, Institute of Language Studies, Unicamp, Brazil. presentation (pdf) (youtube: intro, part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part 9 (takeaway))
	2020     "A new way to find meaningful variation in children’s input across socio-economic status", Linguistics Colloquium, University of California, San Diego. presentation (pdf) (youtube: intro, part 1, part 2, part 3, part 4, part 5, part 6, part 7, part 8, part 9 (takeaway))
	2019     "Using features inspired by psychology and linguistics to improve automatic detection of subtle information in text", Special Guest Speaker Series, Center for Communications Research, La Jolla, CA, and the Institute for Mathematical Behavioral Sciences, University of California, Irvine. presentation (pdf) (youtube: intro, part 1, part 2, takeaway)
	2019     "Arguments from acquisition for how to solve the linking problem", Intended for the Linguistics Colloquium, University of Maryland, College Park (but had to be postponed). presentation (pdf) (youtube: intro, part 1, part 2, takeaway)
	2018     "Quantitative approaches to learning linking theories in language", Institute for Mathematical Behavioral Sciences, University of California, Irvine. presentation (pdf) (youtube: intro, part 1, part 2, takeaway)
	2017     "Using computational modeling to understand language acquisition", Series on Computational Social Science at the University of California. presentation (pdf)
	2017     Lectures on computational models of acquisition, Norwegian Summer Institute on Language and Mind 2017, University of Oslo, Norway. 1: "Introduction to computational models of language acquisition": presentation (pdf) 2: "Computational models of syntactic acquisition": presentation (pdf) 3: "Bayesian inference and linguistic parameters": presentation (pdf)
	2017     "Integrating conceptual and syntactic information to understand the development of English verb classes", Symposium on Advances in Distributional Models of Language and Meaning, joint meeting of the Society for Mathematical Psychology, and the International Conference on Cognitive Modeling, Warwick, UK. abstract || presentation (pdf)
	2017     "The development of verb classes: A computational adventure with implications for linguistic theory", Language Science Colloquium, University of California, Irvine. abstract || presentation (pdf)
	2017     "Computational models of language acquisition: Why, how, and what we can learn", Keynote address at the First Annual Cognitive Science Program Workshop, Simon Fraser University. abstract || presentation (pdf)
	2017     (with Emma Nguyen) "Do you really mean it? Linking lexical semantic profiles and the age of acquisition for the English passive", WCCFL 2017, Calgary, Alberta, Canada. poster (pdf)
	2016     "Integrating conceptual and structural cues: Theories for syntactic acquisition", SynLinks: Links between representation and processing in syntactic acquisition, University of Connecticut, Storrs. abstract || presentation (pdf)
	2016     "Computational model building for acquisition: An introduction", Great Lakes Expo for Experimental and Formal Undergraduate Linguistics, Michigan State University. (Also given at CSU Fullerton for a Child Language lecture in 2016.) presentation (pdf)
	2016     "How to know what’s necessary: Using computational modeling to specify Universal Grammar", Department of Linguistics Colloquium, McGill. abstract || presentation (pdf)
	2016     "The Computation of Language: Syntactic Acquisition Edition", Department of Linguistics Colloquium, UCLA. abstract || presentation (pdf)
	2015     (with Galia Barsever) "Syntactic categories derived from frequent frames benefit early language processing in English and ASL", Boston University Conference on Language Development 40, Boston, MA. abstract
	2015     "Evaluation, use, and refinement of knowledge representations through acquisition modeling", Learning in Generative Grammar: 50 years since the evaluation metric, GALANA, University of Maryland, College Park. abstract || presentation (pdf)
	2014     (with Timothy Ho & Zephyr Detrano) "More learnable than thou? Testing metrical phonology representations with child-directed speech", 40th Annual Meeting of the Berkeley Linguistics Society, UC Berkeley. abstract || presentation (pdf)
	2014     "More learnable than thou? Testing knowledge representations with realistic acquisition data", Linguistics Colloquium, UC Santa Cruz. abstract || presentation (pdf)
	2013     "More learnable than thou? Empirically testing linguistic knowledge representations", Institute for Mathematical Behavioral Sciences Colloquium Series & Logic and Philosophy of Science Colloquium Series, University of California, Irvine. abstract || LPS presentation (pdf)
	2013     "Knowing where to look: Identifying what children need to make syntactic generalizations", Cognition and Language Workshop, Stanford University. abstract || presentation (pdf)
	2013     "Understanding language learning using computational methods", Cognitive Science, Johns Hopkins University, Baltimore, MD. abstract || presentation (pdf)
	2013     "Investigating the development of knowledge using computational methods", Education, Johns Hopkins University, Baltimore, MD. abstract || presentation (pdf)
	2012     "Empirically investigating the Universal Grammar hypothesis", Linguistics Colloquium, New York University. abstract || presentation (pdf)
	2012     "Two good ways to use computational methods to understand language (Acquisition edition)", Mayfest, University of Maryland, College Park. presentation (pdf)
	2012     "Testing the Universal Grammar hypothesis: The contribution of computational modeling", Linguistics Symposium, California State University, Fullerton. abstract || presentation (pdf)
	2012     "Inferring Mental States from Language Text", AI/ML Seminar, Center for Machine Learning & Intelligent Systems, University of California, Irvine. abstract || presentation (pdf)
	2012     (with Jon Sprouse) "Syntactic Islands without Universal Grammar", Workshop on Input & Syntactic Acquisition 2012, Portland, OR. abstract || presentation (pdf)
	2012     (with Lawrence Phillips) "Syllable-based Bayesian inference: A (more) plausible model of word segmentation", 86th Annual Meeting of the Linguistic Society of America, Portland, OR and Workshop on Psychocomputational Models of Human Language Acquisition, Portland, OR. shorter abstract for LSA || presentation (pdf) longer abstract for PsychoCompLA
	2011     (with Benjamin Mis) "How Far Can Indirect Evidence Take Us? Anaphoric One Revisited", 33rd Annual Conference of the Cognitive Science Society, Boston, MA. poster
	2011     (with Michael Lee & Mark Steyvers) "Making Sense of Information Overload", Social Sciences Expert Speaker Series, University of California, Irvine. abstract || presentation (pdf)
	2011     "Looking Beyond: What Indirect Evidence Can Tell Us About Universal Grammar", Workshop on Language, Cognition, and Computation & Workshop on Language, Variation, and Change, University of Chicago. abstract || presentation (pdf)
	2010     "Some Fundamental Issues in Language Acquisition Research and the Contribution of Computational Modeling", guest lecture in Psycholinguistics at the California State University, Fullerton. presentation
	2010     (with Mark Steyvers) "Identifying Emotions, Intentions, & Attitudes in Text Using a Game with a Purpose", NAACL-HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text, Los Angeles, CA. poster
	2010     (with Ivano Caponigro, Neon Brooks, and David Barner) "Acquiring maximality in free relatives and definite descriptions", Semantics and Linguistic Theory 20, Vancouver, British Columbia. abstract || presentation
	2010     "Computation in Acquisition", Linguistics Colloquium, University of Maryland, College Park. abstract || presentation
	2010     (with Ivano Caponigro, Neon Brooks, and David Barner) "On the acquisition of maximality", 36th Incontro di Grammatica Generativa, Universita degli Studi di Milano-Bicocca, Milan, Italy. abstract || poster
	2009     (with Sharon Goldwater and Mark Steyvers) "How Ideal Are We? Incorporating Human Limitations into Bayesian Models of Word Segmentation", Boston University Conference on Language Development 34. abstract || presentation
	2009     (with Sharon Goldwater and Mark Steyvers) "Online Learning Mechanisms for Bayesian Models of Word Segmentation", Psychocomputational Models of Human Language Acquisition workshop, Cognitive Science Annual Conference, VU University Amsterdam, Netherlands. abstract || presentation
	2009     "Parametric Linguistic Systems: The Limits of Probabilistic Learning for Realistic Data", Learning Meets Acquisition workshop at 31st Annual Meeting of Linguistics Association of Germany, University of Osnabrueck, Germany. abstract || presentation
	2009     "Learning-Driven Linguistic Evolution", Social Dynamics Seminar, University of California, Irvine. presentation
	2008     "Learning English Metrical Phonology: Beyond Simple Probability", Generative Approaches to Language Acquisition - North America 3, University of Connecticut, Storrs. abstract || presentation
	2008     "Constrained Probabilistic Learning for Complex Linguistic Systems", Department of Linguistics Colloquium, University of California, San Diego. abstract || presentation
	2008     "Learning-Driven Linguistic Evolution", Workshop on The Evolution of Psychological Categories, Institute for Mathematical Behavioral Sciences, University of California, Irvine. abstract || presentation || video of presentation (.ram)
	2008     "Cognitive Modeling: How Humans Learn Complex Linguistic Systems", Center for Machine Learning and Intelligent Systems AI/ML Seminar Series, University of California, Irvine. abstract || presentation
	2008     "Learning Complex Linguistic Systems: Parameters, Probability, and the Power of Selective Learning", Psychobabble Talk Series, University of California, Los Angeles. presentation
	2007     "An Unambiguous Strategy for Learning Complex Linguistic Systems", Department of Linguistics Colloquium, University of Southern California. abstract || presentation
	2007     "Putting the Emphasis on Unambiguous: The Feasibility of Data Filtering for Learning English Metrical Phonology", Boston University Conference on Language Development 32. abstract || presentation
	2007     "Jack only learns from this data point, but Lily learns from that one, too", Center for Language Sciences, University of Rochester. abstract || presentation
	2007     "Necessary Bias in Natural Language Learning", Thesis Defense, University of Maryland. abstract || presentation
	2007     "Language in Populations: The Interaction Between Learning & Change", Northwestern Institute on Complex Systems, Northwestern University. abstract || presentation
	2007     "At the Interface of Computational Learning Theory and Human Language Learning", Cognitive Sciences, University of California, Irvine. abstract || presentation
	2006     "When domain general learning fails and when it succeeds: Identifying the contribution of domain specificity", Cognitive Neuroscience of Language Lunch Talks, University of Maryland. abstract || presentation
	2006     Bayesian Updating in Human Language Learning, Decisive Analytics Corporation, Arlington, VA. presentation
	2006     Computational Answers to Human Language Learning Questions, National Security Agency, Fort Meade, MD. presentation
	2005     "Generalization, similarity, and Bayesian inference", Language Learning Seminar, University of Maryland. presentation
	2005     The Input for Syntactic Acquisition: Solutions from Language Change Modeling, Psychocomputational Models of Human Language Acquisition workshop, Association for Computational Linguistics, University of Michigan. presentation

	Other Useful Things
	CHILDES Treebank: A collection of child-directed speech from the CHILDES database annotated with phrase structure trees is available here (.zip file). This was generated as part of NSF grant BCS-0843896, "Testing the Universal Grammar Hypothesis", which you can find out more about here, and NSF grant BCS-1347028, "An integrated theory of syntactic acquisition".
	Clarissa Letters Dataset: A collection of all character letters from Samuel Richardson's epistolary novel Clarissa is available here (zipped file). Used for the authorship analyses in Pearl, Lu, & Haghighi (2016).
	Metrical Phonology Compatibility Code: Code for conducting the compatibility analyses described in work by Pearl, Ho, & Detrano is available here (zipped file) and at github.
	Pearl_Brent Phonemes corpus: An English child-directed speech corpus of words transcribed into phonemes is available here (zipped file). This corpus was created from the English Brent corpus of CHILDES and can be used for speech segmentation studies. This is also available through the derived corpus section of the CHILDES database.
	Phillips-Pearl Cross-linguistic Segmentation Corpus: A collection of child-directed speech from seven languages transcribed phonemically and divided into syllables is available here (zipped file). This corpus was created from several corpora from CHILDES and can be used for speech segmentation studies. This is also available through the github.
	UCI_Brent Syllabic corpus: An English child-directed speech corpus of words transcribed into phonemes and divided into syllables is available here (zipped file). This corpus was created from a subsection of the English Brent corpus of CHILDES directed at children 9 months and younger and can be used for word segmentation studies. It also includes the conversion scripts used so this process can be applied to other corpora of interest. This is also available through the derived corpus section of the CHILDES database.
	WordSleuth corpus: Data from the WordSleuth game-with-a-purpose (GWAP), which identifies mental states in language text, is available here (zipped file).