... experimental results for a bilingual cor-
pus are reported.
1.1 Statistical Machine Translation
In statistical machine translation, the goal of the
search strategy can be formulated as follows: ... Section 3.
Source Language
Text
Transformation
1
[ Global Search: -1_ Pr(faIel)
maximize
Pr(el). Pr(f~lel)
over
e I
I
I Transformation
I
1
Target Language
Text
Lex...
... Association for Computational Linguistics:shortpapers, pages 445–449,
Portland, Oregon, June 19-24, 2011.
c
2011 Association for Computational Linguistics
On-line Language Model Biasing for Statistical ... to target
word t
n
in P.
3 Language Model Biasing
In traditional LM training, n-gram counts are evalu-
ated assuming unit weight for each sentence. Our
approach to LM...
... target string
that maximizes the product of the target language
model and the string translation model
.
Many existing systems for statistical machine
translation (Berger et al., 1994; Wang and Waibel,
1997; ... translation probability can be
rewritten as follows:
Source Language Text
Transformation
Lexicon Model
Language Model
Global Search:
Target Language Text...
... 72–80,
Columbus, Ohio, USA, June 2008.
c
2008 Association for Computational Linguistics
Cohesive Phrase-based Decoding for Statistical Machine Translation
Colin Cherry
∗
Microsoft Research
One ... al., 2005). What may have been forgotten during
this transition is that there is a reason it was once be-
lieved that a cohesive translation model would work:
for some language pairs,...
... system for academic research. It consists of
all the components needed to preprocess data, train
the language models and the translation models. It
also contains tools for tuning these models ... Efficient Data Structures for Transla-
tion Model and Language Models
With the availability of ever-increasing
amounts of training data, it has become a challenge
for machine tra...
... results for a Chinese to En-
glish translation task are given.
1 Introduction
Statistical machine translation systems typically
use a translation model trained on bilingual data
and a language model ... Using Noisy Bilingual Data for Statistical Machine Translation
Stephan Vogel
Interactive Systems Lab
Language Technologies Institute
Carnegie Mellon University
vogel+@cs.cm...
... translation model
uses a log-linear approach, in order to combine the
several components, including the language model,
the reordering model, the translation models and the
generation models. The model ... lack of information about its role in the sen-
tence, making it hard to choose the right inflected
forms.
Our method is based on factored phrase-based
statistical machine transl...
...
translation, as performed in A* fashion. This price is
paid for the robustness that is obtained by using very
flexible language and translation models. The lan-
guage model allows sentences ... bracketing transduction gram-
mar (SBTG) model we recently introduced
to replace earlier word alignment channel
models, while retaining a bigram language
model. The new algorithm in o...
...
straightforward way for cross -language docu-
ment summarization is to translate the summary
from the source language to the target language
by using machine translation services. However,
though machine ...
Cross -language document summarization is a
task of producing a summary in one language
for a document set in a different language. Ex-
isting methods simply use m...
... mean average precision for
ranked retrieval, and BLEU or multi-reference word
error rate for statistical machine translation. The use
of statistical techniques in natural language process-
ing ... probabilistic model. Therefore, the fea-
ture functions are much more ’informative’ than for
instance the binary feature functions used in stan-
dard maximum entropy models in natural...