tree alignment 0.00415068
alignment tree 0.00415068
tree alignments 0.0033912400000000002
word alignments 0.0030266499999999997
alignment trees 0.002944391
possible alignment 0.002808476
model probability 0.0028014439999999997
bilingual model 0.0027933759999999998
level alignment 0.002758129
tree node 0.0026866900000000003
cost alignment 0.0026823009999999998
alignment marginals 0.002678118
individual alignment 0.002676886
initial alignment 0.002620063
unlabeled alignment 0.002612616
alignment deci 0.002593612
syntactic alignments 0.0025355539999999998
tree nodes 0.002527819
tree pair 0.002452719
first tree 0.002422483
lexical alignments 0.002356543
tree sampling 0.002352837
alignment 0.00232679
induction model 0.002323607
bayesian model 0.002317735
parsing model 0.00231755
context model 0.00230855
binary tree 0.002303294
english word 0.002298228
gual model 0.002287469
ccm model 0.002280143
true model 0.0022659349999999997
basic model 0.002265881
tree pairs 0.0022587880000000003
model overview 0.002254473
model gains 0.002254207
new tree 0.002176486
original tree 0.002169933
second tree 0.002165303
tree annotations 0.002122796
unaligned tree 0.002118366
vide tree 0.002097332
unordered tree 0.002091092
known tree 0.002091092
possible alignments 0.0020490359999999997
word align 0.0020133399999999997
level alignments 0.0019986889999999997
model 0.00197111
word order 0.001924401
intersection alignments 0.001908761
ical alignments 0.001868331
bad alignments 0.0018508919999999998
tersection alignments 0.001835233
alignments consis 0.001835233
good word 0.0017771179999999998
language training 0.001766543
urdu word 0.001746482
bad word 0.001742842
english sentence 0.00173694
bilingual data 0.001668112
training data 0.001646182
parallel sentence 0.001631889
syntactic structure 0.001595603
syntactic trees 0.001585805
parallel data 0.0015797229999999999
alignments 0.00156735
first language 0.0015647999999999999
other language 0.0015563320000000001
english sentences 0.001534114
node pair 0.001491629
urdu translation 0.001459202
test data 0.001446816
english test 0.001439898
parallel sentences 0.001429063
bilingual distribution 0.001426491
monolingual models 0.001395914
separate tag 0.001384432
monolingual data 0.001362154
parallel trees 0.001351478
parallel corpus 0.001335354
single tag 0.001334692
syntactic structures 0.0013315269999999999
node pairs 0.0012976980000000001
test sentences 0.0012961560000000001
other sentences 0.001285311
parallel text 0.001278649
sentence length 0.0012733850000000001
syntactic annotations 0.00126711
bilingual grammar 0.001266665
maximum sentence 0.001258837
chinese data 0.001258722
ond language 0.001234064
tag sequences 0.001215228
data the 0.001214595
such trees 0.001211228
english ambiguity 0.0012045419999999999
following probability 0.001203515
training time 0.001200807
probabilistic models 0.0011903600000000001
joint probability 0.001181737
