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ACL
2007
13 years 6 months ago
Improved Word-Level System Combination for Machine Translation
Recently, confusion network decoding has been applied in machine translation system combination. Due to errors in the hypothesis alignment, decoding may result in ungrammatical co...
Antti-Veikko I. Rosti, Spyridon Matsoukas, Richard...
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
AI
2009
Springer
13 years 11 months ago
Enhancing the Bilingual Concordancer TransSearch with Word-Level Alignment
Despite the impressive amount of recent studies devoted to improving the state of the art of Machine Translation (MT), Computer Assisted Translation (CAT) tools remain the preferre...
Julien Bourdaillet, Stéphane Huet, Fabrizio...
NAACL
2007
13 years 6 months ago
Combining Outputs from Multiple Machine Translation Systems
Currently there are several approaches to machine translation (MT) based on different paradigms; e.g., phrasal, hierarchical and syntax-based. These three approaches yield similar...
Antti-Veikko I. Rosti, Necip Fazil Ayan, Bing Xian...
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