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» Machine Translation System Combination by Confusion Forest
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NAACL
2004
14 years 11 months ago
A Smorgasbord of Features for Statistical Machine Translation
We describe a methodology for rapid experimentation in statistical machine translation which we use to add a large number of features to a baseline system exploiting features from...
Franz Josef Och, Daniel Gildea, Sanjeev Khudanpur,...
LREC
2010
178views Education» more  LREC 2010»
14 years 11 months ago
Data Issues in English-to-Hindi Machine Translation
Statistical machine translation to morphologically richer languages is a challenging task and more so if the source and target languages differ in word order. Current state-of-the...
Ondrej Bojar, Pavel Stranák, Daniel Zeman
ACL
2001
14 years 11 months ago
Fast Decoding and Optimal Decoding for Machine Translation
A good decoding algorithm is critical to the success of any statistical machine translation system. The decoder's job is to find the translation that is most likely according...
Ulrich Germann, Michael Jahr, Kevin Knight, Daniel...
ACL
2008
14 years 11 months ago
Distributed Word Clustering for Large Scale Class-Based Language Modeling in Machine Translation
In statistical language modeling, one technique to reduce the problematic effects of data sparsity is to partition the vocabulary into equivalence classes. In this paper we invest...
Jakob Uszkoreit, Thorsten Brants
74
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EMNLP
2008
14 years 11 months ago
Maximum Entropy based Rule Selection Model for Syntax-based Statistical Machine Translation
This paper proposes a novel maximum entropy based rule selection (MERS) model for syntax-based statistical machine translation (SMT). The MERS model combines local contextual info...
Qun Liu, Zhongjun He, Yang Liu, Shouxun Lin