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: LinguisTree

Children

Sign in to add trainee
Michelle L. Gregory grad student 2001 CU Boulder (LinguisTree)
Douglas W. Roland grad student 2001 CU Boulder (LinguisTree)
Patrick J. Schone grad student 2001 CU Boulder (LinguisTree)
Noah B. Coccaro grad student 2005 CU Boulder (LinguisTree)
T. Florian Jaeger grad student 2006 Stanford (Neurotree)
Tim Florian Jaeger grad student 2005-2006 Stanford (LinguisTree)
Daniel Cer grad student 2011 CU Boulder (LinguisTree)
Uriel Cohen Priva grad student 2006-2012 Stanford (LinguisTree)
Ruihong Huang post-doc (LinguisTree)
Sebastian Padó post-doc (LinguisTree)
Steven Bethard post-doc 2009-2010 Stanford
BETA: Related publications

Publications

You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect.

Card D, Chang S, Becker C, et al. (2022) Computational analysis of 140 years of US political speeches reveals more positive but increasingly polarized framing of immigration. Proceedings of the National Academy of Sciences of the United States of America. 119: e2120510119
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
See more...