[PDF] Top 20 Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
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Discriminative Training and Maximum Entropy Models for Statistical Machine Translation
... imum entropy training each sentence as reference translation that has the minimal number of word er- rors with respect to any of the reference ... See full document
8
Decoder based Discriminative Training of Phrase Segmentation for Statistical Machine Translation
... phrase-based statistical machine translation (SMT) has been studied by several researchers in recent years (Blackwood et ...the translation fluency despite of the phrase reordering process ... See full document
10
Large Scale Discriminative Training for Statistical Machine Translation Using Held Out Line Search
... in discriminative training for machine translation, large-scale discriminative training with rule indicator features has remained notoriously ...the translation model: ... See full document
11
Improving Alignment Quality in Statistical Machine Translation Using Context dependent Maximum Entropy Models
... ????????? ??? ??????????? ???? ?????????????? ?!?? !"#?$?%?&??"????(')???*???+' ,??? ?? ?&???? ?"$???%?&???? ??"&?? ???')?? ??&?0/1?#243??5?6?5 ?3??5 ??????%/7?8?9??? ?5 ??&????? ?;???13??5??"$< =?>?@[.] ... See full document
7
Hierarchical MT Training using Max Violation Perceptron
... Large-scale discriminative training has be- come promising for statistical machine translation by leveraging the huge train- ing corpus; for example the recent effort in phrase-based MT ... See full document
6
Joint Feature Selection in Distributed Stochastic Learning for Large Scale Discriminative Training in SMT
... of discriminative training for SMT is the possibility to design arbitrarily expres- sive, complex, or overlapping features in great num- ...include Maximum-Entropy Models (Och and Ney, ... See full document
11
Discriminative Feature Tied Mixture Modeling for Statistical Machine Translation
... a maximum-entropy (log-linear) model (Och and Ney, ...phrase translation probabilities, lexical probabilities, number of phrases, and language model scores, ...rate training (MERT) as in (Och, ... See full document
5
Loss Sensitive Discriminative Training of Machine Transliteration Models
... In machine transliteration we transcribe a name across languages while maintaining its phonetic ...of machine transliter- ...Perceptron training in three ways: (1) It allows us to consider k-best ... See full document
5
Minimum Error Rate Training in Statistical Machine Translation
... the training procedure for statisti- cal machine translation models is based on maximum likelihood or related ...final translation quality on unseen ...various training ... See full document
8
Extending Statistical Machine Translation with Discriminative and Trigger Based Lexicon Models
... The models in this paper are also related to word sense disambiguation ...a discriminative model for WSD using local but also across-sentence un- igram collocations of words in order to refine phrase pair ... See full document
9
A Discriminative Latent Variable Model for Statistical Machine Translation
... on discriminative SMT only address some of these ...large training sets (Problem 3); these systems are the local models, for which training is much ...global models (Liang et ...small ... See full document
9
Refined Lexicon Models for Statistical Machine Translation using a Maximum Entropy Approach
... the models and include some semantic and syntactic infor- mation ...another statistical train- ing procedure (Och, 1999) which often pro- duces word classes including words with the same semantic meaning in ... See full document
8
Maximum Entropy Based Phrase Reordering Model for Statistical Machine Translation
... In the experiments described above, collocation features do not make great contributions to the per- formance improvement but make the total num- ber of features increase greatly. This is a prob- lem for MaxEnt parameter ... See full document
8
The Amirkabir Machine Transliteration System for NEWS 2011: Farsi to English Task
... transliteration. Discriminative training is used in our system and numbers of new features are defined in the training ...based statistical translation model is configured to have ... See full document
5
Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation
... mixture models for con- ditional phrase pair probabilities over IN and OUT so as to maximize the likelihood of an empirical joint phrase-pair distribution extracted from a de- velopment ...similar maximum- ... See full document
9
Unsupervised training of maximum entropy models for lexical selection in rule based machine translation
... of maximum entropy has been applied to the problem of lexical selection before; in particular, Berger et ...in statistical MT as a classification ...rate maximum-entropy classifier for ... See full document
8
Maximum Entropy based Rule Selection Model for Syntax based Statistical Machine Translation
... for non-ambiguous source tree will be set to 1.0. Therefore, the decoder will prefer to use non-ambiguous TATs. However, non- ambiguous TATs usually occur only once in the training corpus, which are not reliable. ... See full document
9
Target Side Context for Discriminative Models in Statistical Machine Translation
... Discriminative models in MT have been proposed ...mum entropy classifier for each source phrase type which used source context information to disam- biguate its ...The models did not cap- ture ... See full document
11
A Maximum Entropy Word Aligner for Arabic English Machine Translation
... to machine translation ...the machine translation result on MT03 indicates a slight degradation (al- though it is not statistically ...the training corpus and this process helps good ... See full document
8
Hope and Fear for Discriminative Training of Statistical Translation Models
... ISI machine translation systems, and would not have been possible without my collaborators on those projects: Steve DeNeefe, Kevin Knight, Yuval Marton, Michael Pust, Philip Resnik, and Wei ... See full document
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