[PDF] Top 20 Wider Context by Using Bilingual Language Models in Machine Translation
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Wider Context by Using Bilingual Language Models in Machine Translation
... a bilingual language model that extends the translation model of the phrase-based SMT ap- proach by providing bilingual word ...the bilingual word context, this approach enables ... See full document
9
Dependency Based Bilingual Language Models for Reordering in Statistical Machine Translation
... Our idea is to keep the simplicity of PBSMT but move towards the expressiveness typical of tree- based models. We incrementally build up the syn- tactic representation of a translation during decod- ing by ... See full document
12
Context Dependent Alignment Models for Statistical Machine Translation
... collections, comprising 300k parallel sentence pairs, a to- tal of 8.4M words of Arabic and 9.5M words of English. The Arabic language incorporates into its words sev- eral prefixes and suffixes which determine ... See full document
9
Adaptive Language and Translation Models for Interactive Machine Translation
... on language model adaptation confirmed what had been reported in the literature: adding a cache component to a lan- guage model leads to a drop in ...that using a cache-based language model inside a ... See full document
8
Bilingual Cluster Based Models for Statistical Machine Translation
... the language model weight, minimum error train- ing (Och 2003) with respect to the BLEU score us- ing was conducted using the development ...During translation decoding, the domain spe- cific ... See full document
10
Improve Statistical Machine Translation with Context Sensitive Bilingual Semantic Embedding Model
... words. Bilingual word representations have been presented by Peirsman and Pad´o (2010) and Sumita ...learn bilingual em- beddings utilizes word alignments and monolin- gual embeddings result, Le et ... See full document
5
Large Language Models in Machine Translation
... the context of a particular statis- tical machine translation system, and hints that the third may yet be some time in ...distributed language model training and deployment infrastructure, ... See full document
10
Deep Syntax Language Models and Statistical Machine Translation
... the language model to ensure, that when two phrases are combined with each other, that the model can rank combined phrases that are flu- ent higher than less fluent ...deep context has the potential to ... See full document
9
Deep Neural Language Models for Machine Translation
... Neural language models (NLMs) have been able to improve machine translation (MT) thanks to their ability to generalize well to long ...deep models yield an average boost of ... See full document
5
Statistical Machine Translation with Local Language Models
... Part-of-speech language modeling is com- monly used as a component in statistical ma- chine translation systems, but there is mixed evidence that its usage leads to significant im- ...local language ... See full document
11
Context Adaptation in Statistical Machine Translation Using Models with Exponentially Decaying Cache
... of using these successful tech- niques in SMT is obvious. Language models play a crucial role in fluency ranking and a better fit to real data (supporting the tendency of repetition) should be ... See full document
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Bilingual Structured Language Models for Statistical Machine Translation
... 4 Bilingual structured language models In this section, we combine the direct correspon- dence assumption (Section 2) and SLMs (Sec- tion 3), and define bilingual structured language ... See full document
11
Converting Continuous Space Language Models into N Gram Language Models for Statistical Machine Translation
... The CSLM calculates the probabilities of all words in the vocabulary of the corpus given the context at once. However, because the computational complexity of calculating the probabilities of all words is quite ... See full document
6
Neural Network Transduction Models in Transliteration Generation
... tical machine transliteration system was able to increase the performance of the sys- ...most language pairs which is very promising considering the recency of this ... See full document
6
Learning to translate with products of novices: a suite of open ended challenge problems for teaching MT
... DREAMT is inspired by several different ap- proaches to teaching NLP, AI, and computer sci- ence. Eisner and Smith (2008) teach NLP using a competitive game in which students aim to write fragments of English ... See full document
14
Using First and Second Language Models to Correct Preposition Errors in Second Language Authoring
... out using MT ...second language author, we translate it to the author's L1 language, and then back to ...word translation of ill- formed parts, which mirrors exactly what L2 au- thors do when ... See full document
9
Neural Network Based Bilingual Language Model Growing for Statistical Machine Translation
... n-gram Language Model (LM) usually performs better in Statistical Machine Translation (SMT), how to con- struct efficient large LM is an important topic in ...based bilingual LM growing ... See full document
7
Large and Diverse Language Models for Statistical Machine Translation
... statistical machine trans- lation (SMT) systems have been improved by the use of large language models ...decoder, using them in re-ranking is an ... See full document
6
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
8
Semi Supervised Neural Machine Translation with Language Models
... neural machine translation models is notoriously slow and requires abundant paral- lel corpora and computational ...trained language models to translation systems, also we ... See full document
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