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NiuTrans
mtbookv2
Commits
90361d64
Commit
90361d64
authored
Sep 07, 2020
by
xiaotong
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Merge branch 'master' of 47.105.50.196:NiuTrans/mtbookv2
parents
bf025688
9f04b6e5
隐藏空白字符变更
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2 个修改的文件
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+133
-2
Chapter7/chapter7.tex
+1
-1
bibliography.bib
+132
-1
没有找到文件。
Chapter7/chapter7.tex
查看文件 @
90361d64
...
...
@@ -602,7 +602,7 @@ dr = start_i-end_{i-1}-1
\subsection
{
基于分类的调序
}
\parinterval
在MSD调序中,双语短语所对应的调序概率
$
\funp
{
P
}
(
o
_
i|
\bar
{
s
}_{
a
_
i
}
,
\bar
{
t
}_
i, a
_{
i
-
1
}
, a
_
i
)
$
是用极大似然估计方法进行计算的。但是,这种方法也会面临数据稀疏问题,同时对调序产生影响的细致特征也没有考虑进来。另一种有效的方法是直接用统计分类模型对调序进行建模,比如,可以使用最大熵、SVM等分类器输出调序概率或者得分
\upcite
{
xiong2006maximum,
DBLP:journals/coling/OchN04
,DBLP:conf/naacl/KumarB05
}
。对于基于分类的调序模型,有两方面问题需要考虑:
\parinterval
在MSD调序中,双语短语所对应的调序概率
$
\funp
{
P
}
(
o
_
i|
\bar
{
s
}_{
a
_
i
}
,
\bar
{
t
}_
i, a
_{
i
-
1
}
, a
_
i
)
$
是用极大似然估计方法进行计算的。但是,这种方法也会面临数据稀疏问题,同时对调序产生影响的细致特征也没有考虑进来。另一种有效的方法是直接用统计分类模型对调序进行建模,比如,可以使用最大熵、SVM等分类器输出调序概率或者得分
\upcite
{
xiong2006maximum,
och2004alignment
,DBLP:conf/naacl/KumarB05
}
。对于基于分类的调序模型,有两方面问题需要考虑:
\begin{itemize}
\vspace
{
0.5em
}
...
...
bibliography.bib
查看文件 @
90361d64
...
...
@@ -2081,7 +2081,138 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%% chapter 7------------------------------------------------------
@article{DBLP:journals/tit/Viterbi67,
author = {Andrew J. Viterbi},
title = {Error bounds for convolutional codes and an asymptotically optimum
decoding algorithm},
journal = {IEEE Transactions on Information Theory},
volume = {13},
number = {2},
pages = {260--269},
year = {1967}
}
@inproceedings{DBLP:conf/acl/OchN02,
author = {Franz Josef Och and
Hermann Ney},
title = {Discriminative Training and Maximum Entropy Models for Statistical
Machine Translation},
pages = {295--302},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2002}
}
@inproceedings{koehn2000estimating,
author = {Philipp Koehn and
Kevin Knight},
title = {Estimating Word Translation Probabilities from Unrelated Monolingual
Corpora Using the {EM} Algorithm},
pages = {711--715},
publisher = {AAAI Press},
year = {2000}
}
@inproceedings{dyer2013a,
author = {Chris Dyer and
Victor Chahuneau and
Noah A. Smith},
title = {A Simple, Fast, and Effective Reparameterization of {IBM} Model 2},
pages = {644--648},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2013}
}
@inproceedings{taskar2005a,
author = {Benjamin Taskar and
Simon Lacoste{-}Julien and
Dan Klein},
title = {A Discriminative Matching Approach to Word Alignment},
pages = {73--80},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2005}
}
@inproceedings{DBLP:conf/coling/OchN00,
author = {Franz Josef Och and
Hermann Ney},
title = {A Comparison of Alignment Models for Statistical Machine Translation},
pages = {1086--1090},
publisher = {Morgan Kaufmann},
year = {2000}
}
@inproceedings{koehn2002learning,
author = {Kevin Knight},
title = {Learning a translation lexicon from monolingual corpora},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2002},
pages = {9--16}
}
@inproceedings{Gros2008MSD,
author ={Gros, Jerneja {\v{Z}}ganec},
title ={MSD Recombination Method in Statistical Machine Translation},
volume ={1060},
pages ={186--189},
publisher ={American Institute of Physics},
year ={2008},
}
@inproceedings{xiong2006maximum,
author = {Deyi Xiong and
Qun Liu and
Shouxun Lin},
title = {Maximum Entropy Based Phrase Reordering Model for Statistical Machine
Translation},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2006}
}
@inproceedings{DBLP:conf/naacl/KumarB05,
author = {Shankar Kumar and
William J. Byrne},
title = {Local Phrase Reordering Models for Statistical Machine Translation},
pages = {161--168},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2005}
}
@inproceedings{li-etal-2014-neural,
author = {Peng Li and
Yang Liu and
Maosong Sun and
Tatsuya Izuha and
Dakun Zhang},
title = {A Neural Reordering Model for Phrase-based Translation},
pages = {1897--1907},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2014}
}
@inproceedings{och2003minimum,
author = {Franz Josef Och},
title = {Minimum Error Rate Training in Statistical Machine Translation},
pages = {160--167},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2003}
}
@article{powell1964an,
author = {M. J. D. Powell},
title = {An efficient method for finding the minimum of a function of several
variables without calculating derivatives},
journal = {The Computer Journal},
volume = {7},
number = {2},
pages = {155--162},
year = {1964}
}
@inproceedings{DBLP:conf/emnlp/ChiangMR08,
author = {David Chiang and
Yuval Marton and
Philip Resnik},
title = {Online Large-Margin Training of Syntactic and Structural Translation
Features},
pages = {224--233},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2008}
}
@inproceedings{Hopkins2011Tuning,
author = {Mark Hopkins and
Jonathan May},
title = {Tuning as Ranking},
pages = {1352--1362},
publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2011}
}
%%%%% chapter 7------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
...
...
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