[PDF] Top 20 Using Log-linear Models for Tuning Machine Translation Output
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Using Log-linear Models for Tuning Machine Translation Output
... their log-linear combination is then used to retrieve the best translation paths in the ...function models produce better results than token-based models, 2) adding a PoS-tag feature ... See full document
8
Hope and Fear for Discriminative Training of Statistical Translation Models
... In machine translation, discriminative models have almost entirely supplanted the classical noisy- channel model, but are standardly trained using a method that is reliable only in ... See full document
29
Adaptive Development Data Selection for Log linear Model in Statistical Machine Translation
... for log-linear SMT models, and explain the rationale of task transformation from parameter selection to development data se- ...adapt log-linear model parameters to dif- ferent test ... See full document
9
Pushing the Limits of Translation Quality Estimation
... neural translation models to the APE problem and achieved good results by treating different mod- els as components in a log-linear model, allowing for multiple inputs (the source s and the ... See full document
14
Log linear weight optimisation via Bayesian Adaptation in Statistical Machine Translation
... of log- linear models in SMT are phrase-based (PB) mod- els (Zens et ...PB models allow to capture contextual information to learn translations for whole phrases instead of sin- gle ...PB ... See full document
9
Log-linear Models for Uyghur Segmentation in Spoken Language Translation
... Uyghur machine translation, we proposed a log-linear based morphological segmen- tation ...spoken translation based on both bilingual and monolingual cor- ... See full document
9
Structured Penalties for Log Linear Language Models
... Language models are crucial parts of advanced nat- ural language processing pipelines, such as speech recognition (Burget et ...2007), machine trans- lation (Chang and Collins, 2011), or information ... See full document
11
Log linear Combinations of Monolingual and Bilingual Neural Machine Translation Models for Automatic Post Editing
... for translation in a single state. In- stead, attention models learn to look at particular word states at any position within the source sen- ...these models to learn when to make copies, an ... See full document
8
ListNet based MT Rescoring
... a machine learning perspective the log- linear model is used to solve a ranking ...In machine translation, this ranking is, for example, given by an automatic evaluation ...task. ... See full document
8
Log Linear Models for Word Alignment
... Log-linear models, which are very suitable to in- corporate additional dependencies, have been suc- cessfully applied to statistical machine translation (Och and Ney, ...on ... See full document
8
A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output
... new translation job. We design a machine translation system that operates under similar conditions and explicitly takes an expected level of formality as ... See full document
6
The Effect of Translationese on Tuning for Statistical Machine Translation
... Table 2.1 shows the length ratio of the number of words between the foreign and English side of the tuning and test sets. For all languages there is a large ratio difference depending on the direction of ... See full document
6
Robust Tuning Datasets for Statistical Machine Translation
... the tuning dataset for Statistical Machine Translation (SMT) that makes the hyper-parameters of the SMT system more robust with respect to some specific deficiencies of the parameter tuning ... See full document
8
Batch Tuning Strategies for Statistical Machine Translation
... large-margin tuning methods for SMT that can handle thousands of fea- ...on tuning, and carried out an extensive comparison of linear-loss SMT ... See full document
10
Speed Constrained Tuning for Statistical Machine Translation Using Bayesian Optimization
... Our approach is heavily based on the work of Gelbart et al. (2014) and Hern´andez-Lobato et al. (2015) which uses BO in the presence of unknown constraints. They set speed and memory constraints on neural network ... See full document
10
A Framework for Machine Translation Output Combination
... statistical machine translation system using MOSES [9] trained by the IWSLT07 data is used to determine the alignments between source and target ... See full document
10
Assessing identification risk in survey microdata using log linear models
... of log- linear models to facilitate ...statistical models is well-established in the literature, little consideration has been given to model specification nor to the sensitivity of risk ... See full document
36
Unsupervised Morphological Segmentation with Log Linear Models
... with log-linear models has received little attention in the ...with log-linear models requires computing the normalization constant ... See full document
9
A Virtual Manipulative for Learning Log Linear Models
... ditional log-linear models were first popularized in computational linguistics by a group of re- searchers associated with the IBM speech and lan- guage group, who called them “maximum entropy ... See full document
11
Neural Machine Translation via Binary Code Prediction
... the output layer from ten to one thousand times compared with the standard ...proposed models require only 70% of the actual memory, and the proposed model reduces the to- tal number of parameters for the ... See full document
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