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» Fast Consensus Decoding over Translation Forests
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EMNLP
2008
13 years 6 months ago
Forest-based Translation Rule Extraction
Translation rule extraction is a fundamental problem in machine translation, especially for linguistically syntax-based systems that need parse trees from either or both sides of ...
Haitao Mi, Liang Huang
NAACL
2010
13 years 2 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 ...
ACL
2012
11 years 7 months ago
Learning Translation Consensus with Structured Label Propagation
In this paper, we address the issue for learning better translation consensus in machine translation (MT) research, and explore the search of translation consensus from similar, r...
Shujie Liu, Chi-Ho Li, Mu Li, Ming Zhou
ACL
2008
13 years 6 months ago
Efficient Multi-Pass Decoding for Synchronous Context Free Grammars
We take a multi-pass approach to machine translation decoding when using synchronous context-free grammars as the translation model and n-gram language models: the first pass uses...
Hao Zhang, Daniel Gildea
COLING
2010
12 years 11 months ago
Machine Translation with Lattices and Forests
Traditional 1-best translation pipelines suffer a major drawback: the errors of 1best outputs, inevitably introduced by each module, will propagate and accumulate along the pipeli...
Haitao Mi, Liang Huang, Qun Liu