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LREC
2010
150views Education» more  LREC 2010»
13 years 8 months ago
Achieving Domain Specificity in SMT without Overt Siloing
We examine pooling data as a method for improving Statistical Machine Translation (SMT) quality for narrowly defined domains, such as data for a particular company or public entit...
William D. Lewis, Chris Wendt, David Bullock
ACL
2012
11 years 9 months ago
Fast Syntactic Analysis for Statistical Language Modeling via Substructure Sharing and Uptraining
Long-span features, such as syntax, can improve language models for tasks such as speech recognition and machine translation. However, these language models can be difficult to u...
Ariya Rastrow, Mark Dredze, Sanjeev Khudanpur
EMNLP
2009
13 years 4 months ago
Synchronous Tree Adjoining Machine Translation
Tree Adjoining Grammars have well-known advantages, but are typically considered too difficult for practical systems. We demonstrate that, when done right, adjoining improves tran...
Steve DeNeefe, Kevin Knight
NAACL
2010
13 years 4 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
ACL
2008
13 years 8 months ago
Exploiting N-best Hypotheses for SMT Self-Enhancement
Word and n-gram posterior probabilities estimated on N-best hypotheses have been used to improve the performance of statistical machine translation (SMT) in a rescoring framework....
Boxing Chen, Min Zhang, AiTi Aw, Haizhou Li