letter stress 0.0030517770000000003
english stress 0.003000244
different stress 0.002954394
set stress 0.002944245
stress output 0.00282649
output stress 0.00282649
stress accuracy 0.0027640340000000003
phonetic stress 0.0027518480000000003
possible stress 0.002715528
stress pattern 0.00270768
stress patterns 0.002625122
stress prediction 0.002607322
standard stress 0.002601982
automatic stress 0.002600093
correct stress 0.002595856
common stress 0.0025928590000000003
primary stress 0.002584419
stress rules 0.0025619270000000003
computational stress 0.002557503
svm stress 0.002555668
lexical stress 0.0025276860000000003
perfect stress 0.002513237
regular stress 0.0025045220000000003
combined stress 0.002486514
stress markers 0.002485198
global stress 0.002482925
stress rule 0.002482521
secondary stress 0.002479465
corresponding stress 0.0024775910000000003
stress predictor 0.002474303
full stress 0.002473646
particular stress 0.0024718220000000003
stress ranker 0.0024697630000000003
stress assignment 0.002469345
stress levels 0.002467675
english word 0.002465954
stress predictions 0.002461479
stress annotations 0.002461151
true stress 0.0024603890000000003
accurate stress 0.002458638
ple stress 0.002454112
ways stress 0.002452672
stress regularities 0.002451771
our stress 0.002451397
stress pat 0.002449414
rent stress 0.002448135
oracle stress 0.0024460330000000002
stress placement 0.002445652
late stress 0.002445029
stress marker 0.002444698
stress annota 0.0024444230000000003
stress mark 0.0024429810000000003
training words 0.00241418
word error 0.002389447
word accuracy 0.0022297439999999996
stress 0.00222235
pattern word 0.00217339
human word 0.002139239
prediction word 0.002073032
input word 0.002068247
stressed word 0.0020024319999999997
word forms 0.001995527
word recognition 0.001989115
word splitting 0.00198768
word substrings 0.001971443
tion word 0.001967988
word accu 0.001911102
report word 0.001909746
word etymology 0.001909212
word eco 0.001909212
training data 0.001852544
english training 0.001847844
training sequence 0.0018279260000000001
training set 0.001791845
training error 0.001771337
vocabulary words 0.001613688
same training 0.001598068
letter sequence 0.001587403
written words 0.001573207
different data 0.001514638
other systems 0.00148704
different systems 0.001474809
training patterns 0.001472722
training sets 0.001419408
training pairs 0.001413982
training pair 0.00141273
first system 0.001407785
training framework 0.001398853
first letter 0.001393657
discriminative training 0.0013847680000000002
linear model 0.0013838880000000002
training examples 0.001381997
training time 0.001368763
pattern feature 0.001366115
output sequence 0.001362116
words 0.00134423
letter syllabification 0.0013431889999999998
output set 0.001326035
text feature 0.001322721
generative model 0.001315069
