morphological model 0.002468214
word morphology 0.002202431
model parameters 0.0021271379999999998
generative model 0.002075847
boundary model 0.002071265
order model 0.002050518
probabilistic model 0.002044257
transition model 0.00204115
cal model 0.0019828199999999997
model family 0.001970875
promodes model 0.001956166
model ensemble 0.001910794
der model 0.001903009
other words 0.001830018
certain word 0.001824525
underlying word 0.001821702
cal word 0.00181852
word position 0.001815311
word generation 0.001775276
current word 0.0017652429999999999
word positions 0.0017593829999999998
term word 0.001749961
word decomposition 0.001748443
word list 0.001739057
word decomposi 0.0017383149999999998
model 0.00168382
sible words 0.001319594
zulu words 0.001309885
valid words 0.001303589
morphology learning 0.0012463980000000001
morphological analysis 0.001215229
language description 0.0012133819999999998
african language 0.001155557
input data 0.001134607
rich language 0.001134187
other boundaries 0.001133683
language zulu 0.001127098
agglutinative language 0.001123355
words 0.0010828
other algorithms 0.001075451
labelled data 0.0010619919999999999
unlabelled data 0.0010619919999999999
morphological analy 0.001022376
morphological formation 0.001021474
new algorithm 0.001016564
morphological resources 0.001006365
probabilistic models 0.0010049899999999999
probability distribution 9.718589999999999E-4
ing set 9.45677E-4
learning methods 9.407770000000001E-4
second algorithm 9.35151E-4
learning process 9.34783E-4
supervised algorithm 9.20375E-4
different levels 9.15475E-4
unsupervised learning 9.12856E-4
training set 9.10929E-4
language 9.00013E-4
ukwabelana corpus 8.72039E-4
speech synthesis 8.65388E-4
transition probability 8.39866E-4
boundary vector 8.2849E-4
supervised learning 8.17831E-4
multiple prefixes 8.13788E-4
tial information 8.0057E-4
morpheme boundary 7.967759999999999E-4
morpheme boundaries 7.95796E-4
learning aspect 7.932589999999999E-4
chine learning 7.83149E-4
test set 7.77093E-4
research work 7.65661E-4
possible segmentations 7.656469999999999E-4
generative process 7.63323E-4
set size 7.628610000000001E-4
conditional probability 7.543319999999999E-4
phophonological rules 7.53443E-4
tactical rules 7.53443E-4
previous example 7.47813E-4
single algorithms 7.44322E-4
segment boundaries 7.44162E-4
probabilistic methods 7.377270000000001E-4
abstract morpheme 7.29876E-4
experimental results 7.201169999999999E-4
first component 7.12243E-4
bility distribution 7.08536E-4
same struc 7.05198E-4
competitive results 7.03171E-4
unsupervised version 6.93075E-4
morphology 6.82911E-4
letter transition 6.7858E-4
boundary values 6.784709999999999E-4
unsupervised algorithms 6.77602E-4
indigenous languages 6.76426E-4
boundary value 6.73376E-4
single segmenta 6.67469E-4
algorithm 6.66031E-4
phological analysis 6.65394E-4
related work 6.650580000000001E-4
underlying sequence 6.61401E-4
likelihood estimates 6.59221E-4
ical analysis 6.57309E-4
