[PDF] Top 20 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

... to improve Statistical Machine Translation, which require external data in the form of additional parallel bilingual corpora (Callison-Burch et ...each translation for that ... See full document

... source-language context can be effec- tive in selecting translations in phrase-based and hierarchical ...log-linear model (Gimpel and Smith, 2008; Chiang et al, 2009); predicting co- herent sets of target ... See full document

... Learning semantic representations and tree structures of bilingual phrases is ben- eficial for statistical machine ...network model called Bilingual Corre- spondence Recursive ... See full document

... it semantic vector, in which the grounding space is defined by the given knowledge base, then the same knowledge base and a target monolingual da- ta are used to learn a natural language generator, which produce ... See full document

... a bilingual top- ical admixture formalism for word alignment in ...topic model into language model ...conduct translation model adaptation with monolingual topic ...to improve ... See full document

... based-on statistical approaches (Bassil & Alwani, 2012 and ...2007). Statistical methods use several features, such as N-gram models (Bassil & Alwani, 2012; Islam & Inkpen, 2009), POS tagging ... See full document

... noisy-channel model approach is the independence between decoding and source language probabili- ties, there exists strong evidence on the important role played by source language structure and con- text within ... See full document

... mize the conditional likelihood, we use a version of improved iterative scaling (IIS) coupled with EM which has been used for estimating probabilis- tic unification-based grammars. Unlike the fully- supervised case, the ... See full document

... use machine learning ...ical context features, for integrating information about the neighboring words into a phrase-based SMT system ; and in España-Bonet et ...selection model to address the ... See full document

... on bilingual clustering for sta- tistical machine ...specific translation must be performed simultaneously dur- ing the translation ...a bilingual corpus was clustered using an entropy ... See full document

... We also rescore the n-best lists for the output of the Arabic-English baseline system and results are shown in Table 5. Arabic and English are typolog- ically very different, but the range of reordering is much smaller ... See full document

... Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexan- dra Constantin, and Evan ... See full document

... Language Model (CSLM), especially Neural Network based Lan- guage Model (NNLM) (Bengio et ...or translation model for SMT (Devlin et ... See full document

... of machine transla- ...of machine translation but with typically much smaller vocabulary sizes and no problems related to reordering and in most cases no issues relating to out of vocabulary words ... See full document

... (Air Travel Information Service) (Miller et al., 1996; Papineni et al., 1997; Macherey et al., 2001), in which a typcial MR is only a single semantic frame. Learning methods have been devised that can gen- erate ... See full document

... crowdsourcing machine learning prob- lems: rather than competing, everyone works to- gether to solve a shared task, with credit awarded proportional to the contribution that each individual ... See full document

... Knowledge-based machine translation is the process of applying syntactic knowledge of the source language and semantic knowledge relevant to the source text in order to produce recognized language- ... See full document

... Machine translation system can be formally defined as the task of translating text given in one natural language to others automatically (Koehn, ...(NLP), machine translation system is one of ... See full document

... the translation performance on a small set of paired ...to semantic annotation, the translation relation is monotonic ...the context into account for disambiguation. Note also that the ... See full document