word model 0.00479535
grammar word 0.0036767930000000002
function word 0.003668237
word structure 0.0036475350000000004
word segmentation 0.003581241
word learning 0.0034904840000000003
word class 0.0034406230000000003
word expressions 0.0033759890000000002
rate word 0.003352669
unsupervised word 0.0033473450000000003
word types 0.003337236
word boundaries 0.003336181
word subtrees 0.003320162
bayesian word 0.00331961
corresponding word 0.003315176
specific word 0.003310927
tion word 0.0032910350000000003
content word 0.003281641
word category 0.003260968
word segmentations 0.003239811
terminal word 0.0032345660000000004
word seg 0.00323406
word classes 0.0032296490000000002
word generation 0.003229623
tent word 0.003221652
word book 0.003218565
word segmenta 0.0032158250000000003
models words 0.002769377
function words 0.002653267
context words 0.002584253
grammar model 0.002507503
segmentation model 0.002411951
single words 0.002295038
frequent words 0.002283513
tion words 0.002276065
content words 0.002266671
monosyllabic words 0.002216628
known words 0.002216183
syllabic words 0.0022091560000000003
labic words 0.002202139
bayesian model 0.00215032
tion model 0.002121745
unigram model 0.002121286
baseline model 0.002085452
ore model 0.002083807
peripheral model 0.002078665
model selection 0.002071664
model families 0.002065034
present model 0.002064816
model monosyllables 0.002054593
model selec 0.002045963
model memoises 0.002045963
monkey model 0.002045963
model gen 0.002045963
words 0.00196735
model 0.00181303
grammar models 0.0014965
segmentation models 0.001400948
training corpus 0.001364783
same structure 0.00128731
training data 0.001264292
different mcmc 0.001201874
syntactic structure 0.001170918
bayesian models 0.001139317
adaptor grammar 0.00113908
different procedures 0.001124592
major models 0.001104782
guistic models 0.0010941969999999999
collocation models 0.00109274
different clusters 0.001083649
tional models 0.001072711
computational models 0.001068357
mixture models 0.0010667279999999999
different conso 0.0010656700000000001
rule probability 0.0010652259999999998
grammar inference 0.00106396
complex models 0.001057905
human language 0.0010550400000000001
first rule 0.0010473169999999999
segmentation accuracy 0.001040448
useful approach 0.001038185
parametric models 0.001036398
such claim 0.001008726
syllable structure 0.001006251
frequent function 0.00100208
line grammar 9.90336E-4
target language 9.839340000000001E-4
language acquisition 9.72906E-4
tor grammar 9.72814E-4
hidden structure 9.71616E-4
training sentences 9.63062E-4
peripheral grammar 9.601080000000001E-4
linguistic properties 9.58134E-4
probability vector 9.51662E-4
language acqui 9.49112E-4
grammar software 9.43883E-4
tween function 9.41182E-4
mcmc method 9.38141E-4
full training 9.365339999999999E-4
syllabic grammar 9.36279E-4
