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» Learning Rules to Improve a Machine Translation System
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COLING
2010
13 years 2 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
13 years 2 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...
COLING
2010
13 years 2 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
13 years 8 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»
13 years 5 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