Probabilistic Models in the Study of Language
This textbook covers the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling.
Tag(s): Machine Learning
Publication date: 06 Nov 2012
ISBN-10: n/a
ISBN-13: n/a
Paperback: 274 pages
Views: 5,909
Type: Textbook
Publisher: n/a
License: n/a
Post time: 30 Nov 2016 05:00:00
Probabilistic Models in the Study of Language
This textbook covers the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling.
Publication date: 06 Nov 2012
ISBN-10: n/a
ISBN-13: n/a
Paperback: 274 pages
Views: 5,909
Document Type: Textbook
Publisher: n/a
License: n/a
Post time: 30 Nov 2016 05:00:00
Roger Levy wrote:I'm in the process of writing a textbook on the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling. The intended audience is graduate students in linguistics, psychology, cognitive science, and computer science who are interested in using probabilistic models to study language. Feedback (both comments on existing drafts, and expressed desires for additional material to include!) is more than welcome -- send it to rlevy AT ucsd.edu.
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About The Author(s)
Roger Levy is Associate Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology. Previously, he was Associate Professor in the Department of Linguistics at the University of California, San Diego, where he ran the Computational Psycholinguistics Lab. Currently, he directs MIT's Computational Psycholinguistics Laboratory. His research focuses on theoretical and applied questions in the processing and acquisition of natural language.
Roger Levy is Associate Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology. Previously, he was Associate Professor in the Department of Linguistics at the University of California, San Diego, where he ran the Computational Psycholinguistics Lab. Currently, he directs MIT's Computational Psycholinguistics Laboratory. His research focuses on theoretical and applied questions in the processing and acquisition of natural language.