topic model 0.0032613250000000002
learning model 0.003200362
word learning 0.003131272
bayesian model 0.002941458
model performance 0.002904855
lda model 0.002817855
model setting 0.002800688
mixture model 0.002784429
many word 0.002761856
word contexts 0.002757943
model categorization 0.002753667
tld model 0.0027417730000000003
word tokens 0.0027259040000000003
gold word 0.0027220490000000003
above model 0.002711748
related model 0.002696221
igmm model 0.002689533
ture model 0.002679495
vious model 0.0026758990000000002
model tracks 0.0026748040000000002
word types 0.002641773
word meanings 0.0026273340000000003
word segmenta 0.0026125370000000003
orthographic word 0.002611159
word identities 0.0026058220000000003
word kitty 0.0026058220000000003
model 0.00246669
topic distribution 0.001834745
semantic context 0.0015195439999999998
many words 0.001518816
base distribution 0.001508428
other models 0.001490513
gold words 0.0014790089999999999
function words 0.0014737069999999999
individual words 0.001460619
different categories 0.001457617
specific words 0.001439318
only words 0.001437222
content words 0.001436122
ambiguous words 0.001404752
unintelligible words 0.001364007
own distribution 0.001354348
context information 0.00135088
semantic information 0.001344784
same topic 0.0013324370000000001
different topics 0.001322705
phonetic learning 0.0013015470000000001
learning process 0.001278747
previous models 0.0012784369999999999
discrete distribution 0.001273614
compound distribution 0.001271822
geometric distribution 0.0012685919999999998
topic vector 0.00122283
level models 0.0012215449999999999
similar topic 0.001204826
different mean 0.001198547
topic distributions 0.001186952
learning performance 0.001171837
vowel learning 0.001170522
different lexeme 0.001169277
different situations 0.001168197
recent models 0.0011645639999999999
different vowels 0.001163406
language acquisition 0.001161139
phonetic information 0.0011559349999999999
words 0.00115456
lda topic 0.0011458
different lexemes 0.00114486
lexical context 0.001144639
tld models 0.001143207
distributional learning 0.001133758
learning algorithm 0.001132912
native language 0.001132882
topic dis 0.001131934
topic assignment 0.001128843
different phones 0.0011270479999999999
different sets 0.001123666
models infants 0.001119515
phonetic categories 0.0011179459999999999
conclusion language 0.001113701
corpus statistics 0.001096554
learning setting 0.00106767
semantic knowledge 0.001056994
topic assignments 0.001052233
learning tasks 0.0010500050000000001
semantic meaning 0.001047541
situational context 0.001046714
learning input 0.001046509
final corpus 0.001042808
distribution 0.00104011
current context 0.001038846
prior probability 0.0010381420000000001
other topics 0.0010375480000000001
inference time 0.001036444
linguistic learning 0.0010360859999999999
particular topic 0.001008129
dominant topic 0.00100571
phonetic vowel 0.0010047250000000001
learning problem 0.001001678
brent corpus 9.94338E-4
