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» Diversify and Combine: Improving Word Alignment for Machine ...
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ACL
2012
11 years 7 months ago
Combining Word-Level and Character-Level Models for Machine Translation Between Closely-Related Languages
We propose several techniques for improving statistical machine translation between closely-related languages with scarce resources. We use character-level translation trained on ...
Preslav Nakov, Jörg Tiedemann
COLING
2008
13 years 6 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
EMNLP
2009
13 years 2 months ago
Lattice-based System Combination for Statistical Machine Translation
Current system combination methods usually use confusion networks to find consensus translations among different systems. Requiring one-to-one mappings between the words in candid...
Yang Feng, Yang Liu, Haitao Mi, Qun Liu, Yajuan L&...
TASLP
2008
229views more  TASLP 2008»
13 years 4 months ago
System Combination for Machine Translation of Spoken and Written Language
This paper describes an approach for computing a consensus translation from the outputs of multiple machine translation (MT) systems. The consensus translation is computed by weigh...
Evgeny Matusov, Gregor Leusch, Rafael E. Banchs, N...
ACL
2007
13 years 6 months ago
Tailoring Word Alignments to Syntactic Machine Translation
Extracting tree transducer rules for syntactic MT systems can be hindered by word alignment errors that violate syntactic correspondences. We propose a novel model for unsupervise...
John DeNero, Dan Klein