dialogue act 0.00608452
dialogue corpus 0.005384259
human dialogue 0.005063954
previous dialogue 0.005047855
dialogue acts 0.005004018
appropriate dialogue 0.004998494
automatic dialogue 0.004966334
textual dialogue 0.004931751
messaging dialogue 0.004907612
automated dialogue 0.004903823
dialogue mod 0.004903161
dialogue sys 0.004878779
dialogue macrogame 0.004875459
modelling dialogue 0.004866499
respective dialogue 0.004861495
probable dialogue 0.004860517
dialogue participant 0.004859021
dialogue participants 0.004858454
dialogue 0.00458318
speech act 0.002260755
act sequence 0.001964874
act classification 0.0019379050000000002
act tag 0.001920293
act tagging 0.0018839730000000002
logue act 0.0018757350000000001
act labels 0.001870988
act labelling 0.001862698
act classifier 0.001854071
alogue act 0.0018461620000000002
act boundaries 0.0018138170000000001
act tags 0.001804913
act adjacency 0.0018021
act theory 0.0018000140000000002
act classi 0.0017773650000000002
act classifica 0.001776624
act markup 0.0017762390000000002
act relationship 0.0017757720000000001
dialog act 0.0017757720000000001
act clas 0.0017757720000000001
discourse model 0.001663365
discourse models 0.0016435059999999999
utterance level 0.001606017
discourse understanding 0.001500324
discourse structure 0.001493304
statistical discourse 0.0014643319999999998
current utterance 0.0014362729999999998
labelling task 0.001396288
utterance segmentation 0.001386671
training data 0.001356261
utterance boundaries 0.001352987
utterance boundary 0.001342542
utterance segmen 0.001315784
subjective task 0.0013113620000000002
other types 0.001308711
bigram discourse 0.0013012979999999998
other domains 0.001293154
discourse modelling 0.0012648639999999999
other forms 0.001257864
other studies 0.001243185
multiple utterances 0.00121254
words input 0.001175278
first level 0.001157279
statistical models 0.001144748
large number 0.001137339
several dialogues 0.001132976
statistical approach 0.001125541
previous utterances 0.001122764
many pos 0.001102665
various models 0.001090719
tag set 0.001084778
alistic corpus 0.001077584
tag utterances 0.001077042
single turn 0.001068982
language models 0.0010552489999999999
many tags 0.00105517
clarification question 0.001054068
bayes model 0.001053116
standard set 0.0010473
accuracy results 0.001041746
utterance 0.00104051
nested question 0.001035126
accuracy rate 0.001033085
feature representation 0.001033063
model result 0.0010293569999999998
first message 0.001025912
labelling utterances 0.0010194470000000001
annotation tasks 0.001012691
high accuracy 0.001004373
bigram model 0.001001573
small set 9.985E-4
accidental turn 9.95401E-4
turn interruptions 9.95401E-4
turn msg 9.929930000000002E-4
tagging accuracy 9.87814E-4
model min 9.86264E-4
gram model 9.83321E-4
discourse 9.81545E-4
trigram model 9.79631E-4
mean accuracy 9.76534E-4
total number 9.73759E-4
