E06-1019 proposals to introduce syntax into wordalignment . Someworkwithintheframework
P06-1122 the lexicon mappings during the wordalignment process . The standard SMT lexicon
A94-1006 of part-of-speech tagging and wordalignment programs to extract candidate
P06-1009 Model 4 did not have access to the wordalignments in our training set . Callison-Burch
P06-2124 levels ) . These models enable wordalignment process to leverage topical contents
D11-1108 estimated using Brown et al. ( 1993 ) wordalignment models . These phrase extraction
E14-1001 discriminative step aimed at increasing wordalignment quality on a small , manually
D09-1075 introduce two more refinements to our wordalignment induced tokenization model and
D15-1287 POS-sequence . We fully reconstruct wordalignment for each pair of a source sentence
P04-3019 Corpus ( SPC ) by exploiting the wordalignment technique . The main goal of
E14-2013 be seen as a sub-problem of the wordalignment problem , which is usually solved
E06-2002 parallel corpus provided with wordalignments in both directions , i.e. from
N01-1026 Previously , tools for automatic wordalignment of bilingual corpora were not
P06-1097 on discriminative training for wordalignment differed most strongly from our
N13-1021 open by these results . First , wordalignment models can be extended to process
D15-1143 heuristic rule extraction from the wordalignment decided by derivation trees since
D13-1112 alignment and phrase limit : the wordalignment quality ( typically from GIZA
N10-1014 rules when compared to a standard wordalignment baseline . These high-count rules
N12-1087 agreement constraints between wordalignment directions ( Ganchev et al. ,
D08-1066 provide soft measures for including wordalignments in the estimation process and
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