translation system 0.00411881
translation evaluation 0.0037243599999999995
quality translation 0.003601694
translation quality 0.003601694
machine translation 0.0035721119999999997
translation model 0.003453004
translation systems 0.003375217
reference translation 0.003287979
translation detection 0.0032772089999999997
features data 0.00312754
translation studies 0.0031152669999999997
translation toolkit 0.00306699
relative translation 0.0030612169999999998
translation errors 0.0030562819999999996
chine translation 0.00300944
translation universals 0.003004064
systematic translation 0.0030025739999999996
translation 0.00271072
linguistic features 0.002589423
training data 0.0023873640000000003
system quality 0.002299064
syntactic features 0.002165341
ing features 0.002067282
human evaluation 0.0020613899999999998
cfg features 0.002022425
sentence level 0.002021152
based features 0.002000213
bleu score 0.001997121
mixed features 0.0019922629999999998
special features 0.00197174
independent features 0.0019682659999999998
data google 0.001967076
informed features 0.001939229
ditional features 0.001939229
human quality 0.0019387240000000002
evaluation score 0.0019141409999999998
ing data 0.001904082
source sentence 0.0018972619999999998
smt system 0.0018945140000000001
data points 0.001863061
english sentences 0.001855101
data combinations 0.0018248070000000001
system increases 0.0017026320000000001
sentence instances 0.0016947949999999998
features 0.00164537
other language 0.001628549
function words 0.001627862
human reference 0.0016250090000000002
reference sentences 0.001607089
evaluation scores 0.001563951
feature set 0.00154037
quality correlation 0.001504841
tion words 0.0014830210000000002
different smt 0.001478073
language text 0.0014737259999999999
parallel sentences 0.001455517
output sentences 0.001454741
feature selection 0.0014498129999999999
different sets 0.001441748
target language 0.001437244
english text 0.001422324
monolingual bleu 0.001417018
classification method 0.001414842
system 0.00140809
grammatical words 0.001402176
sentence 0.00137902
evaluation experiments 0.001356857
different amount 0.00134616
human evalu 0.001344979
linguistic fea 0.001342902
statistical machine 0.00134116
machine learning 0.0013341849999999999
ence sentences 0.0013307850000000001
erence sentences 0.001328671
glish sentences 0.00132252
reference translations 0.001315316
estimation score 0.0013145499999999998
quality estimation 0.001305023
estimation method 0.0012961000000000001
detecting different 0.0012857390000000002
feature sets 0.001284149
reference set 0.001283579
various feature 0.001275344
empirical method 0.001268662
tion quality 0.001267055
native language 0.001266171
language pairs 0.001241533
ferent quality 0.001229502
automatic text 0.0012176359999999998
machine transla 0.001213883
such systems 0.001211372
ation score 0.001201726
generic machine 0.001199254
unsupervised quality 0.001182718
tection method 0.0011770209999999999
same corpus 0.001168802
reference corpus 0.0011563609999999998
weka machine 0.00115437
smt systems 0.001150921
experiment set 0.0011480029999999999
