Dan Jurafsky

Affiliations: 
Computer Science Stanford University, Palo Alto, CA 
Area:
natural language understanding
Website:
https://explorecourses.stanford.edu/instructor/jurafsky
Google:
"Dan Jurafsky"
Cross-listing: Computer Science Tree

Parents

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Robert Wilensky grad student 1992 UC Berkeley (Computer Science Tree)

Children

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Michelle L. Gregory grad student 2001 CU Boulder
Douglas W. Roland grad student 2001 CU Boulder
Patrick J. Schone grad student 2001 CU Boulder
Noah B. Coccaro grad student 2005 CU Boulder
T. Florian Jaeger grad student 2006 Stanford
Daniel Cer grad student 2011 CU Boulder
Uriel Cohen Priva grad student 2006-2012 Stanford
Ruihong Huang post-doc
Sebastian Pado post-doc
Steven Bethard post-doc 2009-2010 Stanford (Computer Science Tree)
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Publications

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Mendelsohn J, Tsvetkov Y, Jurafsky D. (2020) A Framework for the Computational Linguistic Analysis of Dehumanization. Frontiers in Artificial Intelligence. 3: 55
Miner AS, Haque A, Fries JA, et al. (2020) Assessing the accuracy of automatic speech recognition for psychotherapy. Npj Digital Medicine. 3: 82
Turnwald BP, Anderson KG, Jurafsky D, et al. (2020) Five-star prices, appealing healthy item descriptions? Expensive restaurants' descriptive menu language. Health Psychology : Official Journal of the Division of Health Psychology, American Psychological Association
Miner AS, Haque A, Fries JA, et al. (2020) Assessing the accuracy of automatic speech recognition for psychotherapy. Npj Digital Medicine. 3: 82
Koenecke A, Nam A, Lake E, et al. (2020) Racial disparities in automated speech recognition. Proceedings of the National Academy of Sciences of the United States of America
Hahn M, Jurafsky D, Futrell R. (2020) Universals of word order reflect optimization of grammars for efficient communication. Proceedings of the National Academy of Sciences of the United States of America
Pryzant R, Diehl Martinez R, Dass N, et al. (2020) Automatically Neutralizing Subjective Bias in Text Proceedings of the Aaai Conference On Artificial Intelligence. 34: 480-489
Lucy L, Demszky D, Bromley P, et al. (2020) Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks: Aera Open. 6: 233285842094031
Garg N, Schiebinger L, Jurafsky D, et al. (2018) Word embeddings quantify 100 years of gender and ethnic stereotypes. Proceedings of the National Academy of Sciences of the United States of America
Prabhakaran V, Griffiths C, Su H, et al. (2018) Detecting Institutional Dialog Acts in Police Traffic Stops Transactions of the Association For Computational Linguistics. 6: 467-481
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