CLAIRE makes machine translation BLEU no more
Name
818354322-MIT.pdf
Description
Full printable version
Size
6.72 MB
Format
Adobe PDF
Checksum (MD5)
abbb1e2354e67342478ce66c39ab7820
Author(s)
Mohammad, Ali (Ali H.)
Advisor(s)
Boris Katz.
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
We introduce CLAIRE, a mathematically principled model for inferring ranks and scores for arbitrary items based on forced-choice binary comparisons, and show how to apply this technique to statistical models to take advantage of problem-specific assistance from non-experts. We apply this technique to two language processing problems: parsing and machine translation. This leads to an analysis which casts doubts on modern evaluation methods for machine translation systems, and an application of CLAIRE as a new technique for evaluating machine translation systems which is inexpensive, has theoretical guarantees, and correlates strongly in practice with more expensive human judgments of system quality. Our analysis reverses several major tenants of the mainstream machine translation research agenda, suggesting in particular that the use of linguistic models should be reexamined.
Description
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 133-139).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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