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» Predicting Success in Machine Translation
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ACL
2007
13 years 9 months ago
Word Sense Disambiguation Improves Statistical Machine Translation
Recent research presents conflicting evidence on whether word sense disambiguation (WSD) systems can help to improve the performance of statistical machine translation (MT) syste...
Yee Seng Chan, Hwee Tou Ng, David Chiang
COLING
2008
13 years 9 months ago
Improving Statistical Machine Translation using Lexicalized Rule Selection
This paper proposes a novel lexicalized approach for rule selection for syntax-based statistical machine translation (SMT). We build maximum entropy (MaxEnt) models which combine ...
Zhongjun He, Qun Liu, Shouxun Lin
ACL
2007
13 years 9 months ago
Tailoring Word Alignments to Syntactic Machine Translation
Extracting tree transducer rules for syntactic MT systems can be hindered by word alignment errors that violate syntactic correspondences. We propose a novel model for unsupervise...
John DeNero, Dan Klein
NAACL
2010
13 years 5 months ago
A Direct Syntax-Driven Reordering Model for Phrase-Based Machine Translation
This paper presents a direct word reordering model with novel syntax-based features for statistical machine translation. Reordering models address the problem of reordering source...
Niyu Ge
LREC
2010
181views Education» more  LREC 2010»
13 years 9 months ago
Linguistically Motivated Unsupervised Segmentation for Machine Translation
In this paper we use statistical machine translation and morphology information from two different morphological analyzers to try to improve translation quality by linguistically ...
Mark Fishel, Harri Kirik