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» Machine Translation System Combination by Confusion Forest
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ACL
2009
13 years 2 months ago
A Comparative Study of Hypothesis Alignment and its Improvement for Machine Translation System Combination
Recently confusion network decoding shows the best performance in combining outputs from multiple machine translation (MT) systems. However, overcoming different word orders prese...
Boxing Chen, Min Zhang, Haizhou Li, AiTi Aw
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...
COLING
2008
13 years 6 months ago
Regenerating Hypotheses for Statistical Machine Translation
This paper studies three techniques that improve the quality of N-best hypotheses through additional regeneration process. Unlike the multi-system consensus approach where multipl...
Boxing Chen, Min Zhang, AiTi Aw, Haizhou Li
COLING
2010
12 years 12 months ago
Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets
An unsupervised discriminative training procedure is proposed for estimating a language model (LM) for machine translation (MT). An English-to-English synchronous context-free gra...
Zhifei Li, Ziyuan Wang, Sanjeev Khudanpur, Jason E...
COLING
2010
12 years 12 months ago
Dependency Forest for Statistical Machine Translation
We propose a structure called dependency forest for statistical machine translation. A dependency forest compactly represents multiple dependency trees. We develop new algorithms ...
Zhaopeng Tu, Yang Liu, Young-Sook Hwang, Qun Liu, ...