[PDF] Top 20 Modeling with Structures in Statistical Machine translation

... It has the following advantages over word-based alignment: • Since the translation model can directly depict phrase reordering in translation, it is more accurate for translation between[r] ... See full document

... Modeling with Structures in Statistical Machine Translation M o d e l i n g w i t h S t r u c t u r e s in S t a t i s t i c a l M a c h i n e T r a n s l a t i o n Y e Y i W a n g and A l e x W a i b[.] ... See full document

... equivalence modeling and statistical machine translation since grammar formalizes what kind of rule to be learned from a parallel ...and statistical machine ...in modeling ... See full document

... Chinese-to-English translation, we use the parallel data from NIST Open Machine Translation Evaluation ...Language Modeling Toolkit, berkeleylm- ...dependency structures of the training ... See full document

... phrase translation model, a lexicalized reordering model, a 6-gram target lan- guage model, distortion cost, word and phrase ...complete translation hypothesis, but it anticipates the gradual accumulation ... See full document

... on statistical machine translation systems began in the early ...which translation of a word or phrase is most likely correct. The translation moves directly from source language to ... See full document

... with about 10M sentence pairs and 300M words in total (counted at the English side). For each sentence in the training, three types of word alignments are created: maximum entropy alignment (Ittycheriah and Roukos, ... See full document

... Predicate-argument structure (PAS) has been demonstrated to be very effective in improving SMT performance. However, since a source- side PAS might correspond to multiple differ- ent target-side PASs, there usually exist ... See full document

... More sophisticated synchronization methods are certainly possible. For example, we could project a part-of-speech tagger (Yarowsky & Ngai, 2001) to improve our estimates in Equation 6. Yet, de- spite their relative ... See full document

... in modeling spurious words, such as function ...improve statistical machine translation performance and also to remove the necessity to model them ...phrase translation should be ... See full document

... individual structures will somehow fall into place ...both translation and evaluation. At translation time, domain adaptation techniques increase the likelihood of correct translations on average, ... See full document

... et al., 2007), which included a large amount of manual work. Graham and van Genabith (2008) and Graham et al. (2009) explored the automatic rule induction approach in a transfer-based MT setting involving two lexical ... See full document

... the modeling of natural language from a computational ...few machine translation systems are also developed in Malayalam for translating Malayalam to English and vice versa but these are not offered ... See full document

... Nowadays statistical machine translation shows its benefits and has received much ...phrase-based statistical machine translation was carefully ...phrase structures, and ... See full document

... This paper describes the algorithms and features we used in the WMT 13 Quality Estimation tasks. In the sentence-level QE task (Task 1.1), we de- velop an enhanced version of BLEU metric, and this shows a potential usage ... See full document

... of machine translation is greatly improved by applying neural networks par- tially in a Statistical Machine Translation (SMT) pipeline (Zou et ...based machine translation ... See full document

... One avenue of SMT research has been to add as many features as possible to the linear model, es- pecially in the form of sparse features (Chiang et al., 2009; Hopkins and May, 2011; Cherry and Fos- ter, 2012; Gimpel and ... See full document

... We run ParFDA SMT experiments for all lan- guage pairs in both directions in the WMT15 translation task (Bojar et al., 2015), which include English-Czech (en-cs), English-German (en-de), English-Finnish (en-fi), ... See full document

... In order to train these classifiers, we have to col- lect training events from our word-aligned bilin- gual training data where source words are anno- tated with their corresponding sense clusters pre- dicted by the ... See full document

... them. So as to translate longer sequences, the decoder combines these partial n-gram trans- lations, and ranks the resulting candidates ac- cording to their corresponding scores and the rest of scoring functions. In ... See full document