[PDF] Top 20 Investigating continuous space language models for machine translation quality estimation
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Investigating continuous space language models for machine translation quality estimation
... prediction quality, either when used separately or in ...prediction models, despite their simplicity and the fact that they require only monolingual data as resource, which is available in abundance for ... See full document
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Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation
... In an 1000-best list for 586 sentences, we have a total of 14M requests for 7-grams out of which more than 13.5M were processed by the CSLM, e.g. the short list hit rate is almost 95%. This resulted in only 2670 forward ... See full document
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Continuous Space Translation Models with Neural Networks
... neural translation model, implemented here in the framework of the n-gram based models, tak- ing advantage of a specific hierarchical architecture ...gual translation models were presented and ... See full document
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SHEF LIUM NN: Sentence level Quality Estimation with Neural Network Features
... on Quality Estimation. Our submissions use (i) a continuous space language model (CSLM) to extract sentence embeddings and cross-entropy scores, (ii) a neural net- work machine ... See full document
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Ensembling Factored Neural Machine Translation Models for Automatic Post Editing and Quality Estimation
... Level Quality Estimation (QE) using en- sembles of specialized Neural Machine Translation (NMT) ...the machine translation hypothesis, which are used to generate an automati- ... See full document
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Parser Accuracy in Quality Estimation of Machine Translation: A Tree Kernel Approach
... tag language model probabilities of the MT output ...builds models for estimating post-editing effort using syntactic features such as parse probabilities and label ... See full document
5
Proceedings of the Third Conference on Machine Translation: Research Papers
... three translation tasks: Machine Translation of News, Biomedical Translation, and Multimodal Machine Translation, two evaluation tasks: Metrics and Quality ... See full document
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Continuous Space Translation Models for Phrase Based Statistical Machine Translation
... The translation model P ( s | t ) is estimated from bitexts and the language model P ( t ) from monolingual ...phrase-based models which translate short sequences of words together (Koehn et ...The ... See full document
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Tree Kernels for Machine Translation Quality Estimation
... our Machine Learning (ML) component, we used tree kernel ...ture space whose dimensions correspond to all pos- sible tree ...source language, and doubtful syntactic structures in the output ... See full document
5
Converting Continuous Space Language Models into N Gram Language Models for Statistical Machine Translation
... Language models are important in natural language processing tasks such as speech recognition and statistical machine ...n-gram language models (BNLMs) (Chen and Goodman, 1996; ... See full document
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Continuous Space Language Models for Statistical Machine Translation
... In this work, a slightly different procedure was used that operates directly on the translation lat- tices. We believe that this is more efficient than reranking n-best lists since it guarantees that al- ways all ... See full document
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Multi level Translation Quality Prediction with QuEst++
... Document-level QE consists in predicting a sin- gle label for entire documents, be it an absolute score (Scarton and Specia, 2014) or a relative ranking of translations by one or more MT sys- tems (Soricut and Echihabi, ... See full document
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Machine Translation Quality Estimation Across Domains
... MT quality prediction demonstrated to be useful for different applications, such as: deciding whether the translation output can be published without post-editing (Soricut and Echihabi, 2010), filtering out ... See full document
12
Improving Evaluation of Machine Translation Quality Estimation
... and to demonstrate the ability of evaluation of sys- tems trained on a representation distinct from that of gold labels made possible by the unit-free Pear- son correlation, we also include evaluation of sys- tems ... See full document
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Learning to translate with products of novices: a suite of open ended challenge problems for teaching MT
... chine translation should be good paraphrases of each other (Owczarzak et ...between machine translation and reference under a simple model in which words could align if they were ... See full document
14
Multiple stream Language Models for Statistical Machine Translation
... The results show that even with a large amount of static data adding small amounts of stream spe- cific data relevant to a given test point has an im- pact on translation quality. Compared to only us- ing ... See full document
10
Large and Diverse Language Models for Statistical Machine Translation
... To assess the utility of re-ranking with large LMs, we carried out a number of experiments, summa- rized in Table 4. We used the English side of the par- allel training corpus and the Gigaword corpus dis- tributed by the ... See full document
6
Deep Syntax Language Models and Statistical Machine Translation
... Hierarchical Models increase the re- ordering capabilities of MT systems by introducing non-terminal symbols to phrases that map source language (SL) words/phrases to the correct position in the target ... See full document
9
Black Box Features for the WMT 2012 Quality Estimation Shared Task
... 2. Translation features model the connection be- tween source and ...chine translation, the advantage in confidence estimation is that we can exercise unconstruc- tive criticism, ... See full document
5
LIMSI @ WMT13
... back-off language models (BOLMs), have been introduced in (Bengio et ...crete language models ...n-gram models that use large vocabulary, thereby making the training of large neural ... See full document
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