Spoken Dialogue Systems (LSA 353), Regular Session, 5-27 July |
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TTh 10-12 |
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Professor: |
Office Hours: |
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Email: |
julia [at] cs.columbia.edu |
Phone: |
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Course Areas: Computational Linguistics, Discourse
All are available on line, linked to this syllabus.
Copying or paraphrasing someone's work (code included), or permitting your own work to be copied or paraphrased, even if only in part, is not allowed, and will result in an automatic grade of 0 for the entire assignment or exam in which the copying or paraphrasing was done. Your grade should reflect your own work. If you believe you are going to have trouble completing an assignment, please talk to the professor in advance of the due date.
Week |
Date |
Topic |
Readings and Assignments |
Reports and HW |
1 |
F Jul 6 |
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2 |
Tu Jul 10 |
J&M 22.1 (new version); Clark03; Beattie82 |
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F Jul 13 |
J&M 22.2 (new version) |
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3 |
Tu Jul 17 |
J&M 22.4,8 (new version); Walkeretal97 |
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F Jul 20 |
J&M 22.5 (new version);Jurafsky98, Rosset&Lamel04 |
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4 |
T Jul 24 |
J&M 22.5 (new version); Hirschbergetal04, Goldberg03, Krahmer01 |
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F Jul 27 |
J&M 22.2 (new version); Brennan96; Roth05 |
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A term paper, 8-10 pages long, on the following topic:
- –Identify 5 or more strategies you can use to demonstrate that Eliza is not a human conversationalist (e.g. linguistic constructions she does not handle well, pragmatic behaviors she does not generate appropriately or recognize). As evidence describe your inputs and her outputs
- Explain the difficulties you will have to overcome in recognition, generation, and dialogue management, compared to the text version, based upon the topics we have studied in class and additional observations you may have
- –Suggest specific ways of dealing with these problems based upon what you know of the state of the art in SDS or ideas you may have to improve upon it
- Indicate the ways in which a spoken version of Eliza might be even better than the text version, in terms of how it might interact with the user and the features of spoken language you might be able to make use of in generation and recognition of user behavior