Automatic correction of grammatical errors in non-native English text
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2010
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| Online Access: | http://hdl.handle.net/1721.1/53292 |
| _version_ | 1826189683948781568 |
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| author | Lee, John Sie Yuen, 1977- |
| author2 | Stephanie Seneff. |
| author_facet | Stephanie Seneff. Lee, John Sie Yuen, 1977- |
| author_sort | Lee, John Sie Yuen, 1977- |
| collection | MIT |
| description | Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. |
| first_indexed | 2024-09-23T08:19:28Z |
| format | Thesis |
| id | mit-1721.1/53292 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T08:19:28Z |
| publishDate | 2010 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/532922022-01-13T07:54:29Z Automatic correction of grammatical errors in non-native English text Lee, John Sie Yuen, 1977- Stephanie Seneff. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Electrical Engineering and Computer Science. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. Cataloged from PDF version of thesis. Includes bibliographical references (p. 99-107). Learning a foreign language requires much practice outside of the classroom. Computer-assisted language learning systems can help fill this need, and one desirable capability of such systems is the automatic correction of grammatical errors in texts written by non-native speakers. This dissertation concerns the correction of non-native grammatical errors in English text, and the closely related task of generating test items for language learning, using a combination of statistical and linguistic methods. We show that syntactic analysis enables extraction of more salient features. We address issues concerning robustness in feature extraction from non-native texts; and also design a framework for simultaneous correction of multiple error types. Our proposed methods are applied on some of the most common usage errors, including prepositions, verb forms, and articles. The methods are evaluated on sentences with synthetic and real errors, and in both restricted and open domains. A secondary theme of this dissertation is that of user customization. We perform a detailed analysis on a non-native corpus, illustrating the utility of an error model based on the mother tongue. We study the benefits of adjusting the correction models based on the quality of the input text; and also present novel methods to generate high-quality multiple-choice items that are tailored to the interests of the user. by John Sie Yuen Lee. Ph.D. 2010-03-25T15:27:14Z 2010-03-25T15:27:14Z 2009 2009 Thesis http://hdl.handle.net/1721.1/53292 549097733 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 107 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Lee, John Sie Yuen, 1977- Automatic correction of grammatical errors in non-native English text |
| title | Automatic correction of grammatical errors in non-native English text |
| title_full | Automatic correction of grammatical errors in non-native English text |
| title_fullStr | Automatic correction of grammatical errors in non-native English text |
| title_full_unstemmed | Automatic correction of grammatical errors in non-native English text |
| title_short | Automatic correction of grammatical errors in non-native English text |
| title_sort | automatic correction of grammatical errors in non native english text |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/53292 |
| work_keys_str_mv | AT leejohnsieyuen1977 automaticcorrectionofgrammaticalerrorsinnonnativeenglishtext |