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» Learning Rules to Improve a Machine Translation System
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COLING
2010
14 years 4 months ago
Dependency-Based Bracketing Transduction Grammar for Statistical Machine Translation
In this paper, we propose a novel dependency-based bracketing transduction grammar for statistical machine translation, which converts a source sentence into a target dependency t...
Jinsong Su, Yang Liu, Haitao Mi, Hongmei Zhao, Yaj...
COLING
2010
14 years 4 months ago
Log-linear weight optimisation via Bayesian Adaptation in Statistical Machine Translation
We present an adaptation technique for statistical machine translation, which applies the well-known Bayesian learning paradigm for adapting the model parameters. Since state-of-t...
Germán Sanchis-Trilles, Francisco Casacuber...
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COLING
2010
14 years 4 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
COLING
2000
14 years 11 months ago
Chart-Based Transfer Rule Application in Machine Translation
35"ansfer-based Machine Translation systems require a procedure for choosing the set; of transfer rules for generating a target language translation from a given source langu...
Adam Meyers, Michiko Kosaka, Ralph Grishman
MT
2010
134views more  MT 2010»
14 years 8 months ago
Improve syntax-based translation using deep syntactic structures
This paper introduces deep syntactic structures to syntax-based Statistical Machine Translation (SMT). We use a Head-driven Phrase Structure Grammar (HPSG) parser to obtain the de...
Xianchao Wu, Takuya Matsuzaki, Jun-ichi Tsujii