[PDF] Top 20 Deep Syntax Language Models and Statistical Machine Translation
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Deep Syntax Language Models and Statistical Machine Translation
... string-based language model provides as good if not better context than the deep syntax model, but only for the few words that happen to be preceded by words that are important to its lexical choice, ... See full document
9
Converting Continuous Space Language Models into N Gram Language Models for Statistical Machine Translation
... Another approach is using restricted Boltzmann machines (RBMs) (Niehues and Waibel, 2012) instead of using multi-layer neural networks (Bengio et al., 2003; Schwenk, 2007; Le et al., 2011). Since probability in a RBM can ... See full document
6
Distortion Models for Statistical Machine Translation
... Existing statistical machine translation decoders have mostly relied on language models to select the proper word order among many possible choices when translating between two ...a ... See full document
8
Discontinuous Statistical Machine Translation with Target Side Dependency Syntax
... this translation model al- ready proved to be useful when translating from English into German, Chinese, and Arabic as demonstrated by Seemann et ...suited syntax-based translation model for those ... See full document
9
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring
... German-Czech language pair are built based on the previously proposed unsupervised MT sys- tems, with some adaptations made to accom- modate the morphologically rich characteristics of German and Czech (Tsarfaty ... See full document
8
Bilingual Structured Language Models for Statistical Machine Translation
... ditional syntax-based LM. In this section, we de- scribe a syntactic language model, structured LM (SLM) (Chelba and Jelinek, 2000), that we extend to a bilingual setting and apply to SMT in Sec- tion ... See full document
11
Large and Diverse Language Models for Statistical Machine Translation
... Often more data is better data, and so it should come as no surprise that recently statistical machine trans- lation (SMT) systems have been improved by the use of large language models (LM). ... See full document
6
A Study of Translation Rule Classification for Syntax based Statistical Machine Translation
... SMT models is that they can not effectively model the discontiguous translations and numerous at- tempts have been made on this issue (Simard et ...the translation rule in Figure 3(b) is an actual ... See full document
6
Example based Machine Translation Based on Syntactic Transfer with Statistical Models
... and translation) are obtained from child ...the translation probabil- ity is calculated, the source word sub-sequence is obtained by tracing transfer mapping, and the ap- plied translation model is ... See full document
7
Dependency Based Bilingual Language Models for Reordering in Statistical Machine Translation
... In statistical machine translation (SMT) reorder- ing (also called distortion) refers to the order in which source words are translated to generate the translation in the target ...English ... See full document
12
Surveys: A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena
... lexicalized translation rules. This is a major difference with respect to most syntax-based approaches, where reordering can be captured by rules containing only labeled non-terminals ...hierarchical ... See full document
43
Factored models for Deep Machine Translation
... Bulgarian language encodes definiteness as an ending to the nouns and adjectives in contrast to English which encodes it as a separate determiner in front of the noun or ... See full document
9
Context Adaptation in Statistical Machine Translation Using Models with Exponentially Decaying Cache
... of language and translation models to a new domain using the cache-based mixture models as described ...phrase translation cache within the Moses ...cache models on or off using ... See full document
8
Fast Translation Rule Matching for Syntax based Statistical Machine Translation
... We carry out experiment on Chinese-English NIST evaluation tasks. We use FBIS corpus (250K sentence pairs) as training data with the source side parsed by a modified Charniak parser (Charniak 2000) which can output a ... See full document
9
Deep Neural Language Models for Machine Translation
... We gratefully acknowledge support from a gift from Bloomberg L.P. and from the Defense Advanced Research Projects Agency (DARPA) Broad Operational Language Translation (BOLT) program under contract ... See full document
5
Statistical Machine Translation with Local Language Models
... POS language models depends among other things on the size of the parallel cor- pus, the size and order of the word language model, and whether lexicalized distortion models are ...guage ... See full document
11
Language Model Adaptation for Statistical Machine Translation via Structured Query Models
... query models and retrieved the top 4000 relevant sentences from AFE corpus for each source ...these language models, interpolated with the background language model gave a NIST score of ... See full document
7
Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation
... Language models play an important role in large vocabulary speech recognition and sta- tistical machine translation ...guage models trained on hundreds of billions of ...large ... See full document
9
MoL 2015 08: Modelling Syntactic and Semantic Tasks with Linguistically Enriched Recursive Neural Networks
... natural language is a diverse but fruitful field of research which spans multiple ...on machine learning techniques to capture the phenomenon and generally finds it difficult to capture edge cases; instead ... See full document
83
Syntax Based Word Ordering Incorporating a Large Scale Language Model
... A fundamental problem in text generation is word ordering. Word ordering is a com- putationally difficult problem, which can be constrained to some extent for particu- lar applications, for example by using syn- chronous ... See full document
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