[PDF] Top 20 Learning for Semantic Parsing with Statistical Machine Translation
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Learning for Semantic Parsing with Statistical Machine Translation
... tical machine translation techniques. More specif- ically, a statistical word alignment model (Brown et ...a parsing framework called the synchronous CFG (Aho and Ullman, 1972), which forms ... See full document
8
Active Learning for Multilingual Statistical Machine Translation
... Statistical machine translation (SMT) models require bilingual corpora for train- ing, and these corpora are often multi- lingual with parallel text in multiple lan- guages ...active learning ... See full document
9
Online Learning for Statistical Machine Translation
... online learning techniques for statistical machine translation ...of translation agencies or the daily translation of government ...batch learning techniques require very ... See full document
41
Non linear Learning for Statistical Machine Translation
... Modern statistical machine translation (SMT) systems usually use a linear com- bination of features to model the quality of each translation ...A learning framework is presented for ... See full document
11
Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision
... to learning the event-type selection probabilities, ...generative semantic parsing model, which is also trained in several steps in its best-performing ver- ... See full document
9
A Statistical Machine Translation Model with Forest-to-Tree Algorithm for Semantic Parsing
... for semantic parsing with statistical machine translation, our semantic pars- ing framework consists of two main ...linearized semantic parses, given by an off-the-shelf ... See full document
6
Transductive learning for statistical machine translation
... We ran our initial experiments on EuroParl to ex- plore the behavior of the transductive learning algo- rithm. In all experiments reported in this subsec- tion, the test set was used as unlabeled data. The ... See full document
8
Graph based Learning for Statistical Machine Translation
... The synthetic nodes and edges need to be added to prevent the label propagation algorithm from con- verging to the trivial solution that assigns r = 1 to all points in the graph. This choice is theoretically motivated—a ... See full document
9
Name Translation in Statistical Machine Translation Learning When to Transliterate
... 3. On the fly, we add transliterations to SMT phrase table. Instead of a phrasal probability, the transliterations have a special binary feature set to 1. In a tuning step, the Minimim Error Rate Training component of ... See full document
9
Online Learning for Interactive Statistical Machine Translation
... line learning for IMT is (Cesa-Bianchi et ...online learning is not able to extend the translation models due to technical problems with the efficiency of the learning ...purely ... See full document
9
Generation by Inverting a Semantic Parser that Uses Statistical Machine Translation
... Parsing with W ASP requires a set of SCFG rules. These rules are learned using a word alignment model, which finds an optimal mapping from words to MR predicates given a set of training sentences and their correct ... See full document
8
Active Learning for Statistical Phrase based Machine Translation
... Statistical machine translation (SMT) mod- els need large bilingual corpora for train- ing, which are unavailable for some language ...active learning for SMT. We use active learning to ... See full document
9
Tutorial: De mystifying Neural MT
... Neural Statistical Machine Translation Neural Machine Translation Encoder Decoder Sequence-to-sequence learning: Encoder Sequence-to-sequence learning: Decoder Let’s use a simple NN for [r] ... See full document
84
Neural Machine Translation for Bilingually Scarce Scenarios: a Deep Multi Task Learning Approach
... Neural machine translation requires large amounts of parallel training text to learn a reasonable-quality translation ...the machine translation task on auxiliary tasks including ... See full document
10
Language to Code: Learning Semantic Parsers for If This Then That Recipes
... Vector Machine (SVM) to introduce productions in the derivation of the formal ...like semantic concepts to be recognized from natural-language ...ing semantic parsing, these classifiers are ... See full document
11
A Semantic Feature for Statistical Machine Translation
... A semantic feature for statistical machine trans- lation, based on Latent Semantic Indexing, is proposed and ...to statistical machine ...each translation unit in the ... See full document
9
Non Projective Parsing for Statistical Machine Translation
... of the source-language string. As one set of exam- ples, consider the translations in figure 3, and the example given in the introduction. These exam- ples involve reordering of arguments and adjuncts within clauses, a ... See full document
10
Statistical Machine Translation by Parsing
... Figure 7 is only an architecture. Computational complexity and generalization error stand in the way of its practical implementation. Nevertheless, it is satisfying to note that all the non-trivial algo- rithms in Figure ... See full document
8
Semantic Parsing as Machine Translation
... tsVB also uses a piece of standard MT ma- chinery, specifically tree transducers, which have been profitably employed for syntax-based ma- chine translation (Maletti, 2010). In that work, however, the usual MT ... See full document
6
Improving Statistical Machine Translation with Processing Shallow Parsing
... As mentioned in section 1, some approaches us- ing syntactic information are applied to solve the reordering problem. One of approaches is syntac- tic parsing of source language and reordering rules as ... See full document
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