[PDF] Top 20 A non contiguous Tree Sequence Alignment based Model for Statistical Machine Translation

... in statistical machine translation (SMT) mostly settles itself in the domain of either phrase-based or ...and contiguous phrase ...with non- contiguous phrases. To address ... See full document

... identical translation, we cannot use BLEU as the error criterion any ...Instead, alignment F-score is used as the alterna- ...step, alignment quality can be improved by replacing original alignments ... See full document

... for tree-to-string models, making use of parse trees for one of the two languages, and tree-to-tree models, which make use of parallel parse ...of alignment error rate indicate that the clone ... See full document

... high translation quality, it still lacks of generaliza- tion ability to capture word order differences between ...for tree-to-string phrase- based ...and non-constituent phrasal translations ... See full document

... trigram model in machine translation, Ding and Palmer (2005) use n-gram rule Markov model in the dependency treelet model, Liu and Gildea (2008) applies the same method in a ... See full document

... ficiently model several syntactic features, includ- ing long-distance ...Regular Tree Languages (RTLs), which can represent Context-free Languages (CFLs) since a set of all syntactic trees of a CFL is an ... See full document

... the statistical alignment models used to obtain a word alignment and techniques for learning phrase translations from word ...consecutive sequence of words occurring in text and has to be ... See full document

... suggested translation (Simard and Isa- belle, ...a Translation-Services Provider (TSP) company to reliably determine in advance the increase in translator productivity due to the use of MT and to adjust ... See full document

... our model is that TATs can be automatically acquired to capture linguistically motivated reordering at both low (word) and high (phrase, clause) ...TAT-based model is less computationally expen- sive ... See full document

... noisy-channel model to transfer a target parse tree into a source ...learn non-isomorphic tree-to-tree/string mappings using a ...tion model based on a probabilistic ... See full document

... Statistical Machine Translation (SMT) is based on alignment models which learn from bilingual corpora the word correspondences between the source and target ...Recursive ... See full document

... 4 compares WordSys to our proposed system. Sig- nificant testing was carried out using bootstrap re-sampling method proposed by Koehn (2004) with a 95% confidence level. We see that our pro- posed systems outperformed ... See full document

... paper dvi A Comparison of Alignment Models for Statistical Machine Translation Franz Josef Och and Hermann Ney Lehrstuhl f?ur Informatik VI, Computer Science Department RWTH Aachen University of Techn[.] ... See full document

... Word alignment is a crucial early step in the training of most statistical machine translation (SMT) sys- tems, in which the estimated alignments are used for constraining the set of ... See full document

... ing statistical techniques and shallow linguistic pro- cessing applied on a bilingual parallel corpus of software documentation which is sentence-aligned, POS-tagged and shallow ...clause alignment ... See full document

... weighted alignment matrices, we fol- lowed Venugopal et ...two translation direc- ...symmetric alignment. As different alignment pairs might produce the same symmetric align- ments, we ... See full document

... reordering model fails to filter out bad large- scale reorderings effectively (Koehn ...the translation accuracy drop because of search errors (Koehn et ...better translation accuracy than the ... See full document

... actor alignment in English and Bengali phrase based Statistical Machine Translation (PB-SMT) ...identified based on the concept of complex predicate ...hybrid alignment ... See full document

... in statistical machine transla- tion (SMT) (Brown et ...in translation lexicon building (Melamed 1996), transfer rule learning (Menezes and Richardson 2001), example-based machine ... See full document

... (ME) model algo- rithm to estimate their reordering probabilities sep- arately, where the boundary words of foreign phrases and candidate target translation phrases, POS information and dependencies are ... See full document