[PDF] Top 20 Dynamically Shaping the Reordering Search Space of Phrase Based Statistical Machine Translation

... early reordering pruning to be effective, it is especially important that the correct reordering option be ranked in the top n among those available at the time of a given hypoth- esis ... See full document

... range reordering of verbs, in particular, represents a real challenge for state-of-the- art SMT systems and is one of the main reasons why translation quality is often so poor in this language ...of ... See full document

... Word reordering is one of the most difficult aspects of Statistical Machine Translation (SMT), and an important factor of its quality and ...range reordering is reasonably handled by ... See full document

... local phrase reorder- ing models developed for use in statistical machine ...the Translation Template Model to perform phrase alignment and translation using standard WFST op- ... See full document

... use phrase-based statistical machine translation (PSMT) to translate between language pairs which require long-range re- ordering has attracted a great deal of interest in re- cent ... See full document

... In Statistical Machine Translation (SMT), the constraints on word reorderings have a great impact on the set of potential translations that are ...the reordering space of a SMT system ... See full document

... The search for consistent Viterbi phrase align- ments can be implemented as a phrase-based de- coder using a beam search whose outputs are con- strained only to the target ...N-best ... See full document

... word-based reordering model into hierarchical phrase-based machine translation ...the search space of ...Eisner’s reordering model for our method, but ... See full document

... phrasal reordering is totally dependent on the language model (NONE) we get the worst performance, even worse than the monotone ...distortion reordering models (Row 3 and 4) show similar performance with ... See full document

... hierarchical phrase-based translation model (HPTM) reorganizes phrases into hierarchical ones by reducing sub-phrases to variables (Chiang ...entropy-based reordering model (MEBTG). ... See full document

... Single-Word Based Systems (SWB). First, there is a monotone search variant (Mon) that translates each word of the source sentence from left to ...allows reordering according to the so-called IBM con- ... See full document

... of phrase pairs and the most likely translation provided by the ...these phrase pairs are included in the training data. The standard Moses phrase table only contains many single word-to-word ... See full document

... ming search algorithm exists as described in the previous ...or phrase by phrase. The idea is to start with the beam search decoder for unconstrained search and modify it in such a way ... See full document

... that reordering rules learned from automatic alignments lead to significantly better translation than rules learned from manual ...larger search space, which in turn means more proposed trans- ... See full document

... extending Phrase-based Statistical Machine Translation (PBSMT) with syntactic structure caused system per- formance to ...measure based on combina- tory ... See full document

... We used these three corpora to extract a set of sentences that were aligned to each other across all four languages. For that purpose, we used English as the pivot. For each distinct English sentence, we extracted the ... See full document

... contemporary machine translation paradigm, and to experiment with a broader range of ...automatic translation of a sentence in a given language from a partic- ular ...include translation among ... See full document

... man, 2000), a word-centered syntax that allows a great deal of flexibility in how sentence analyses are formed. Syntactic derivations in CCG are mas- sively spuriously ambiguous, i.e., there are many ways to derive the ... See full document

... combining translation memory (TM) and statistical machine translation (SMT) when the TM database and the SMT training set are the ...we dynamically merge the matched TM ... See full document

... We used 1 million sentence pairs that are con- tained in train-1.txt of ASPEC-JE corpus for training the translation rule tables and NMT models. We also used 3 million Japanese sen- tences that are contained in ... See full document