[PDF] Top 20 Factored models for Deep Machine Translation
Has 10000 "Factored models for Deep Machine Translation" found on our website. Below are the top 20 most common "Factored models for Deep Machine Translation".
Factored models for Deep Machine Translation
... the factored-based MOSES ...model translation experience described in (Wang et ...Bulgarian-to-English translation was explored, in this paper also the English-to-Bulgarian direction is ... See full document
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Deep Syntax Language Models and Statistical Machine Translation
... (and deep syntactic struc- tures in general) was possibly overlooked ...a deep syntax language model, we ensure that such du- plicate ngrams are omitted in training and ...bigram deep syntax language ... See full document
9
Factored Statistical Machine Translation for Grammatical Error Correction
... a factored statistical machine translation (SMT) model for this ...language translation problems guided by various linguistic information, as factors that influence translation ...of ... See full document
8
Factored Soft Source Syntactic Constraints for Hierarchical Machine Translation
... distortion models (Koehn et ...reordering models (Koehn et ...reordering models (Galley and Manning, 2008; Cherry, 2013) that handle reordering prefer- ences beyond adjacent ...cal translation ... See full document
11
Ensembling Factored Neural Machine Translation Models for Automatic Post Editing and Quality Estimation
... Martins et al. (2016) introduced a stacked archi- tecture, using a very large feature set within a structured prediction framework to achieve a large jump in the state of the art for Word-Level QE. Some features are ... See full document
8
Deep Recurrent Models with Fast Forward Connections for Neural Machine Translation
... neural models have been studied in a wide range of ...vision, models with more than ten convolution layers outperform shallow ones on a series of image tasks in recent years (Srivastava et ...training ... See full document
14
A Hybrid Approach for Deep Machine Translation
... for deep MT was presented in the language direction from English to ...the translation model, suggesting a two- level transfer ...the factored MT ... See full document
8
Word Transduction for Addressing the OOV Problem in Machine Translation for Similar Resource Scarce Languages
... statistical translation models that easily inte- grates additional linguistic informations as ...This factored parallel corpus was then used to train the translation model us- ing the SMT ... See full document
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Exploiting Deep Representations for Neural Machine Translation
... Multi-layer network can be considered as a strong feature extractor with extended receptive fields capable of linking salient features from the entire sequence (Chen et al., 2018). However, one potential problem about ... See full document
10
Factored Translation with Unsupervised Word Clusters
... of translation quality with plenty of bilingual text and a translation model that maps small chunks of tokens as they appear in the surface form, that is, the usual phrase-based sta- tistical machine ... See full document
5
Phrase Based Query Degradation Modeling for Vocabulary Independent Ranked Utterance Retrieval
... OOV, we must use vocabulary-independent tech- niques to locate them. One popular approach is to search for the words in output from a phoneme rec- ognizer (Ng and Zue, 2000), although this suffers from the low accuracy ... See full document
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Comparing a Hand crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation
... of machine translation (MT) has proven to be a very significant research ...statistical machine translation (SMT) model and the other from a neural machine translation (NMT) ... See full document
9
Morphological Segmentation and OPUS for Finnish English Machine Translation
... the translation between Finnish and English using standard tech- nology such as phrase-based and factored statisti- cal machine translation, in preparation for a more focused future effort in ... See full document
7
Pragmatic Neural Language Modelling in Machine Translation
... In this section, we are concerned with finding scal- able training algorithms for neural language mod- els. We investigate noise contrastive estimation as a much more efficient alternative to standard maxi- mum ... See full document
10
Learning Deep Transformer Models for Machine Translation
... We report the ablation study results in Table 6. We first observe a modest decrease when removing the introduced layer normalization in Eq. (8). Then we try two methods to replace learnable weights with constant weights: ... See full document
13
Deep Neural Language Models for Machine Translation
... has been an active body of work recently in uti- lizing neural language models (NLMs) to improve translation quality. However, to the best of our knowledge, work in this direction only makes use of NLMs ... See full document
5
Word Representations in Factored Neural Machine Translation
... The encoder and the attention mechanism of the Factored NMT are the same as the standard NMT model. However, the decoder has been modified to produce multiple outputs. The two outputs are constrained to have the ... See full document
12
Factored Translation Models
... model: Translation options in this model may come either from the surface form model or from the lemma/morphology model we just de- ...different translation tables form dif- ferent components in the ... See full document
9
MATREX: The DCU MT System for WMT 2010
... We used the output of 15 systems for sys- tem combination for the en–cs translation task. Among these, 5 systems were built using Moses and varying the size of the training data (DCU- All, DCU-Ex2M, DCU-4M, DCU-2M ... See full document
6
Cross Corpora Evaluation and Analysis of Grammatical Error Correction Models — Is Single Corpus Evaluation Enough?
... other models in the highest and the lowest error-rated corpora, respec- ...oriented models have an advantage over recall- oriented models when a given text contains sev- eral errors, and vice ... See full document
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