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NAACL
1994
15 years 2 months ago
The Automatic Component of the LINGSTAT Machine-Aided Translation System
We present the newest implementation of the LINGSTAT machine-aided translation system. The moat signiflcsat change from earlier versions is a new set of modules that produce a dra...
Jonathan Yamron, James Cant, Anne Demedts, Taiko D...
91
Voted
ACL
2007
15 years 2 months ago
Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora
Current phrase-based SMT systems perform poorly when using small training sets. This is a consequence of unreliable translation estimates and low coverage over source and target p...
Trevor Cohn, Mirella Lapata
ACL
2010
14 years 11 months ago
Diversify and Combine: Improving Word Alignment for Machine Translation on Low-Resource Languages
We present a novel method to improve word alignment quality and eventually the translation performance by producing and combining complementary word alignments for low-resource la...
Bing Xiang, Yonggang Deng, Bowen Zhou
126
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NAACL
2010
14 years 10 months ago
Model Combination for Machine Translation
Machine translation benefits from two types of decoding techniques: consensus decoding over multiple hypotheses under a single model and system combination over hypotheses from di...
John DeNero, Shankar Kumar, Ciprian Chelba, Franz ...
89
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COLING
2008
15 years 2 months ago
Improving Alignments for Better Confusion Networks for Combining Machine Translation Systems
The state-of-the-art system combination method for machine translation (MT) is the word-based combination using confusion networks. One of the crucial steps in confusion network d...
Necip Fazil Ayan, Jing Zheng, Wen Wang