[PDF] Top 20 Applying Morphological Decompositions to Statistical Machine Translation

... to-English translation tasks of the ACL 2010 Joint Fifth Workshop on Statistical Machine Translation and ...MetricsMATR. Statistical machine translation has focused on ... See full document

... of morphological informa- tion, especially for morphologically rich languages, the requirement for training data might be much re- ...German-English statistical MT with limited bilingual training data ... See full document

... In [6] Och and Ney first introduced the log-linear model into SMT. Koehn suggested using features of lexical weighting. In 2004, the famous phrase-based decoder, Pharaoh [7], was released to be a free SMT toolkit by ... See full document

... augmented statistical machine translation model from Bulgarian to English, which combines a statistical machine translation (SMT) system (as backbone) with deep lin- guistic ... See full document

... A complicating factor is that the binarization should not impair the RDLM. During decoding, we map the internal tree structure of each hypoth- esis back to the unbinarized form, which is then scored by the RDLM. Virtual ... 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, Alexandra Constantin, and Evan ... See full document

... that Statistical Machine Translation will be an easier affair on this ...the morphological richness of Marathi makes it as difficult as any other Indian language to Indian language ... See full document

... these kinds of translation results have difficulty conveying the meaning of the original sentences. So, the sentences under 2.5 have little improvements by SPE. Meanwhile, in the case of the translation ... See full document

... Boosting (Schapire, 1990) constructs a strong learner by repeatedly choosing a weak learner and applying it on a re-weighted training set. In each iteration, a weak model is learned on the training data, whose ... See full document

... given translation task allows us to train higher order language models, model longer range dependencies better, and achieve lower perplexity as shown in Table ...a morphological analyzer and disambiguator ... See full document

... subsequent translation into Czech is achieved using two phrase-based translation sys- ...reference) translation of the head of its English ...the morphological layer ... See full document

... and statistical analysis to identify the five- factor structure, calculate reliability, and examine ...a statistical approach to extract common factors across measured variables based on correlation ... See full document

... For example: the gloss ‘he who studies’ tries to mimic a relative construct which is represented as one word in Tamil. The pronominal information in ‘patikkiRavan’ (‘he who studies’) indicates that the word refers to a ... See full document

... as morphological and orthographic processing (Nießen and Ney, 2004; Lee, 2004; Goldwater and McClosky, 2005; Oflazer and Durgar El-Kahlout, 2007; Stymne, 2012; Singh and Habash, 2012; Habash and Sadat, 2012; El ... See full document

... novel morphological analysis technique which induces a morphological and syntactic symmetry between two languages with highly asymmetrical morphological structures to improve statistical ... See full document

... Our training data amounts to around 50 mil- lion bilingual sentences overall, but we conduct sets of experiments with systems trained using different fractions of this data (50K, 500K, 5M, 50M). Whereas English→Czech has ... 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 ... See full document

... most machine translation research has focused on resource-rich settings where NMT has indeed superseded SMT, a recent line of work has managed to train an NMT system without any supervision, relying on ... See full document

... The class of synchronous parsers includes some algorithms for word alignment. A translation lexi- con (weighted or not) can be viewed as a degenerate MTG (not in GCNF) where every production has a link of ... See full document

... Although our work is framed with respect to MERT, the convex geometric description is also applicable to other error-based training methods for linear models. We believe our analysis has important ramifications because ... See full document