def __init__( self, feature_type_list, skype_contacts_dict=None ):
# --- COMMON --- #
# These internal state you probably want in any dialog manager
self._processed_nbest_event_handler_list = []
self._processed_audio_event_handler_list = []
self._operate_phone_event_handler_list = []
self.feature_type_list = feature_type_list
# --- CUSTOM --- #
# These internal state are specific to this dialog manager
self.system_state = 'sleeping'
self.window_size = 50;
self.audio_power_list = [];
# For our simple dialog system, we have a confirmation buffer
# the user needs to confirm in order to complete the above action
self.confirmation_buffer = None
if skype_contacts_dict != None:
self.skype_contacts_dict = skype_contacts_dict
else:
self.skype_contacts_dict = None
# --- CUSTOM --- #
# This is for the POMDP dialog manager
dialog_data = tbh_pomdp_util.get_matlab_dialog_data( DIALOG_DATA_PATH )
self.pomdp = tbh_pomdp_util.get_pomdp( dialog_data )
self.Q = tbh_pomdp_util.get_Q( dialog_data )
self.pomdp.belief = self.pomdp.start_dist[ :, 0 ]
self.machine_action = None
def __init__( self, feature_type_list, dialog_data_path = DIALOG_DATA_PATH, \
skype_contacts_dict=None, \
high_confidence_histogram = None, \
low_confidence_histogram = None ):
# --- COMMON --- #
# These internal state you probably want in any dialog manager
self._processed_nbest_event_handler_list = []
self._processed_audio_event_handler_list = []
self._operate_phone_event_handler_list = []
self.feature_type_list = feature_type_list
# --- FOR EXPERIMENTS --- #
self._experiment_event_handler_list = []
# --- CUSTOM --- #
# These internal state are specific to this dialog manager
self.system_state = 'sleeping'
self.window_size = 50;
self.audio_power_list = [];
# for confidence modeling
self.high_confidence_histogram = high_confidence_histogram
self.low_confidence_histogram = low_confidence_histogram
# For our simple dialog system, we have a confirmation buffer
# the user needs to confirm in order to complete the above action
self.confirmation_buffer = None
if skype_contacts_dict != None:
self.skype_contacts_dict = skype_contacts_dict
else:
self.skype_contacts_dict = None
# --- CUSTOM --- #
# This is for the POMDP dialog manager
dialog_data = tbh_pomdp_util.get_matlab_dialog_data( dialog_data_path )
self.pomdp = tbh_pomdp_util.get_pomdp( dialog_data )
self.Q = tbh_pomdp_util.get_Q( dialog_data )
self.machine_action = None
# FOR EXPERIMENTS
self.experiment_controller = \
tbh_experiment_controller.experiment_controller()
self.current_experiment_log = None
"""
def __init__( self, feature_type_list, dialog_data_path = DIALOG_DATA_PATH, skype_contacts_dict=None ):
# --- COMMON --- #
# These internal state you probably want in any dialog manager
self._processed_nbest_event_handler_list = []
self._processed_audio_event_handler_list = []
self._operate_phone_event_handler_list = []
self.feature_type_list = feature_type_list
# --- CUSTOM --- #
# These internal state are specific to this dialog manager
self.system_state = 'sleeping'
self.window_size = 50;
self.audio_power_list = [];
# For our simple dialog system, we have a confirmation buffer
# the user needs to confirm in order to complete the above action
self.confirmation_buffer = None
if skype_contacts_dict != None:
self.skype_contacts_dict = skype_contacts_dict
else:
self.skype_contacts_dict = None
# --- CUSTOM --- #
# This is for the POMDP dialog manager
dialog_data = tbh_pomdp_util.get_matlab_dialog_data( dialog_data_path )
self.pomdp = tbh_pomdp_util.get_pomdp( dialog_data )
if USE_DATA_OBSERVATION_FUNCTION:
#print "#### USING DATA OBSERVATION FUNCTION ####"
#print self.pomdp.nrObservations[[0]]
#print int( self.pomdp.nrGeneralActions )
states = range( pomdp.nrStates )
actions = range( pomdp.nrActions )
states = range(0,96)
actions = range(0,101)
import pickle
f = open( '../../dialog_system_tools/src/observation_model.pkl', 'r' )
normalized_final_model = pickle.load( f )
for s in states:
for a in actions:
self.pomdp.observation[s][a] = normalized_final_model[s]
else:
pass
#print "#### ENTIRE OBSERVATION FUNCTION ###"
#print self.pomdp.observation
self.Q = tbh_pomdp_util.get_Q( dialog_data )
self.machine_action = None
best_qmdp_value = qmdp_value
elif qmdp_value > best_qmdp_value:
best_action = i
best_qmdp_value = qmdp_value
return best_action
if __name__ == '__main__':
#solve_qmdp( [], [], [] )
#test_pomdp = pomdp( nrStates=3, nrActions=2 )
#matlab_policy = numpy.genfromtxt( 'policy.txt', dtype=int )
#Q = numpy.genfromtxt( 'Q.txt' )
dialog_data = tbh_pomdp_util.get_matlab_dialog_data( 'dialog_data.mat' )
#matlab_policy = dialog_data['policy']
Q = dialog_data['Q']
#print matlab_policy
#print Q
nrStates = Q.shape[0]
nrActions = Q.shape[1]
dialog_pomdp = pomdp( nrStates, nrActions )
belief_vector = numpy.ones( [1, nrStates ] )
belief_vector = belief_vector * 1/nrStates
#print belief_vector
