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Overcoming the customization bottleneck
using example-based MT
July 1, 2001
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Download Document
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View Link
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BibTex
Authors

Stephen D. Richardson

Bill Dolan

Arul Menezes

Monica Corston-Oliver
Publication Type
Inproceedings
Publisher
Association for Computational Linguistics
All copyrights reserved by ACL 2001.

Abstract

Related Info
Abstract
We describe MSR-MT, a large-scale hybrid machine translation system under development for
several language pairs. This system’s ability to acquire its primary translation knowledge
automatically by parsing a bilingual corpus of hundreds of thousands of sentence pairs and
aligning resulting logical forms demonstrates true promise for overcoming the so-called MT
customization bottleneck. Trained on English and Spanish technical prose, a blind evaluation
shows that MSR-MT’s integration of rule-based parsers, example based processing, and
statistical techniques produces translations whose quality exceeds that of uncustomized
commercial MT systems in this domain.
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 Natural Language Processing
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 Machine Translation
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 Natural language processing and speech
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 Microsoft Research Lab - Redmond
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