Sciweavers

41 search results - page 6 / 9
» Dependency Forest for Statistical Machine Translation
Sort
View
84
Voted
EMNLP
2008
14 years 11 months ago
Online Large-Margin Training of Syntactic and Structural Translation Features
Minimum-error-rate training (MERT) is a bottleneck for current development in statistical machine translation because it is limited in the number of weights it can reliably optimi...
David Chiang, Yuval Marton, Philip Resnik
ACL
2010
14 years 7 months ago
Importance of Linguistic Constraints in Statistical Dependency Parsing
Statistical systems with high accuracy are very useful in real-world applications. If these systems can capture basic linguistic information, then the usefulness of these statisti...
Bharat Ram Ambati
ACL
2009
14 years 7 months ago
Forest-based Tree Sequence to String Translation Model
This paper proposes a forest-based tree sequence to string translation model for syntaxbased statistical machine translation, which automatically learns tree sequence to string tr...
Hui Zhang, Min Zhang, Haizhou Li, AiTi Aw, Chew Li...
ACL
2010
14 years 7 months ago
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models
We present cdec, an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based m...
Chris Dyer, Adam Lopez, Juri Ganitkevitch, Jonatha...
71
Voted
LREC
2010
213views Education» more  LREC 2010»
14 years 11 months ago
Active Learning and Crowd-Sourcing for Machine Translation
In recent years, corpus based approaches to machine translation have become predominant, with Statistical Machine Translation (SMT) being the most actively progressing area. Succe...
Vamshi Ambati, Stephan Vogel, Jaime G. Carbonell