stress model 0.00364127
grammar word 0.00359449
syllable stress 0.00317759
word segmentation 0.003172937
word sequences 0.002957694
english word 0.002910111
grammar model 0.00280335
word boundaries 0.002784719
actual word 0.00277534
word tokens 0.002725803
strong word 0.002720724
word seg 0.002720251
word types 0.002689073
true word 0.00267945
valid word 0.002674995
stress information 0.0025714889999999997
stress system 0.00253024
english stress 0.002484321
segmentation model 0.0023817969999999997
dictionary stress 0.0023283229999999998
stress cues 0.002290763
stress inter 0.002287011
stress cue 0.002271754
typical stress 0.0022687939999999998
stress constraint 0.0022520599999999997
tract stress 0.002251407
stress identification 0.002251407
incorporated stress 0.002248922
stress obser 0.002248922
unique stress 0.002248922
stress 0.00200331
unigram model 0.0019937369999999998
bigram model 0.001905937
srn model 0.001883942
training data 0.001845876
adaptor grammar 0.001659369
first syllable 0.001649611
model 0.00163796
syllable onsets 0.0015876599999999999
initial syllable 0.001545603
syllable weight 0.001535699
second syllable 0.001535553
syllable codas 0.001530863
syllable nodes 0.001509405
grammar framework 0.001503407
cation grammar 0.00149251
stressed syllable 0.001490019
basic syllable 0.001445562
syllable shapes 0.001418873
segmentation models 0.001401132
entire words 0.001399944
monosyllabic words 0.001389011
segmentation accuracy 0.0013206720000000002
probability distribution 0.001231298
corpus size 0.001194589
same information 0.001180665
syllable 0.00117428
grammar 0.00116539
words 0.00112539
learning problem 0.001117319
providence corpus 0.00109009
different modeling 0.001077717
test set 0.001066504
training 0.00106632
input size 0.0010241529999999999
real speech 0.00102321
ing input 0.001006317
different ways 0.001005712
different tokens 0.001002857
probabilistic models 9.95398E-4
lexical forms 9.94401E-4
true segmentation 9.941870000000001E-4
speech recognition 9.91699E-4
ment speech 9.7957E-4
different contexts 9.666239999999999E-4
input sizes 9.55645E-4
adaptor grammars 9.53779E-4
phonetic reflexes 9.521950000000001E-4
learning curve 9.49762E-4
consonant coda 9.496840000000001E-4
useful information 9.28359E-4
tional models 9.20634E-4
base distribution 9.204629999999999E-4
language acquisition 9.202100000000001E-4
trival learning 9.103500000000001E-4
putational models 9.0354E-4
first experiment 8.99294E-4
bayesian adaptor 8.97559E-4
long vowel 8.96207E-4
phonological patterns 8.90606E-4
same infor 8.80981E-4
initial syllables 8.80789E-4
pcfg rules 8.792030000000001E-4
initial onset 8.68183E-4
same batch 8.60977E-4
pcfg rule 8.579810000000001E-4
cial set 8.563050000000001E-4
single pcfg 8.46463E-4
corpus 8.44336E-4
computational results 8.417380000000001E-4
