[PDF] Top 20 A Semantic Feature for Statistical Machine Translation
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A Semantic Feature for Statistical Machine Translation
... Some output sentences were randomly selected, regardless of which system performed better, for conducting a manual inspection. From these sen- tences, we have extracted some segments that illus- trate specific cases in ... See full document
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A Statistical Machine Translation Model with Forest-to-Tree Algorithm for Semantic Parsing
... Now we present the algorithm for semantic pars- ing, which translates NL sentences into LFs us- ing a reduction-based λ-SCFG. It is based on an extended version of a reduction-based SCFG (Lu and Ng, 2011). Given a ... See full document
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Arabic-English Semantic Word Class Alignment to Improve Statistical Machine Translation
... The aim of this step is to identify the semantic concepts of the English side of the parallel corpus. The manual determination of these concepts is a very heavy task, so we should find an automatic method to ... See full document
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Fast and Adaptive Online Training of Feature Rich Translation Models
... We present a fast and scalable online method for tuning statistical machine trans- lation models with large feature sets. The standard tuning algorithm—MERT—only scales to tens of features. Recent ... See full document
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Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus
... a machine translation task, where an SCFG is used to model the translation of an NL into a formal meaning-representation lan- guage ...uses statistical models developed for syntax-based SMT ... See full document
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Improve Statistical Machine Translation with Context Sensitive Bilingual Semantic Embedding Model
... Using vectors to represent word meanings is the essence of vector space models (VSM). The representations capture words’ semantic and syn- tactic information which can be used to measure semantic ... See full document
5
Enriching Parallel Corpora for Statistical Machine Translation with Semantic Negation Rephrasing
... Our experiments with the phrase-based SMT sys- tem Moses show small improvements over the base- line considering the entire test data. A more dis- tinct look at only negated sentences in the test data shows a ... See full document
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Multi Pass Decoding With Complex Feature Guidance for Statistical Machine Translation
... The IN configuration, which puts in a trans- lation table all bi-phrases in the one-best hy- pothesis of Rerank that do not belong to the Moses one-best hypothesis, performs the best for all translation tasks: ... See full document
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Linguistically Augmented Bulgarian to English Statistical Machine Translation Model
... The first model is served as the baseline here. We show all the n-gram scores besides the final BLEU, since the some of the differences are very small. In terms of the numbers, POS seems to be an effective factor, as ... See full document
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Paraphrasing Out of Vocabulary Words with Word Embeddings and Semantic Lexicons for Low Resource Statistical Machine Translation
... To further understand the reason of the improvement, we analyzed the translation difference between Baseline and Word2vec retrofitted by PPDB. Figure 2 shows two trans- lation examples. In example 1, the Baseline ... See full document
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Feature Decay Algorithms for Fast Deployment of Accurate Statistical Machine Translation Systems
... use feature decay algorithms (FDA) for fast deployment of accurate statistical machine translation systems taking only about half a day for each translation direc- ...accurate ... See full document
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Corpus Expansion for Statistical Machine Translation with Semantic Role Label Substitution Rules
... to Semantic Role Labeling (Palmer et ...and semantic constraints to select the ...based translation models and bilingual lan- guage models to identify high quality sentence pairs, and use these ... See full document
5
On Statistical Machine Translation and Translation Theory
... in translation studies, which has been named the cultural turn (Lefevere and Bassnett, 1995; Snell-Hornby, ...key feature of more recent theoretical approaches to translation is their emphasis on the ... See full document
5
Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation
... White and Baldridge (2003) for CCG. More re- cently, statistical chart generators have emerged, in- cluding White (2004) for CCG, Carroll and Oepen (2005) and Nakanishi et al. (2005) for HPSG. Many of these ... See full document
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Discriminative Feature Tied Mixture Modeling for Statistical Machine Translation
... phrase translation probabilities, lexical probabilities, number of phrases, and language model scores, ...The feature weights are usually optimized with min- imum error rate training (MERT) as in (Och, ... See full document
5
LSTM Neural Reordering Feature for Statistical Machine Translation
... We present a novel work that build a reordering model using LSTM-RNN, which is much sensitive to the change of context and introduce rich con- text information for reordering prediction. Further- more, the proposed model ... See full document
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Towards Efficient Large Scale Feature Rich Statistical Machine Translation
... This phenomenon is further evident in German when testing each model on Test2, which is se- lected from the bitext, and is thus closer matched to the larger tuning sets, but is separate from both the parallel data used ... See full document
6
Phrase Based Statistical Machine Translation: A Level of Detail Approach
... the translation of a phrase using the word-based translation ...literal translation of phrase constituents is often in- appropriate from a linguistic point of ...word-based translation model ... See full document
12
Learning for Semantic Parsing with Statistical Machine Translation
... shallow semantic analysis, such as semantic role labeling and word-sense disam- ...of semantic parsing, which is the con- struction of a complete, formal, symbolic, mean- ing representation (MR) of a ... See full document
8
Structural Feature Selection For English Korean Statistical Machine Translation
... coling dvi Structural Feature Selection For English Korean Statistical Machine Translation Seonho Kim, Juntae Yoon, Mansuk Song fpobi, jtyoon, mssongg@december yonsei ac kr Dept of Computer Science, Y[.] ... See full document
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