def fetch_initial_statement():
# generate_speech() is the function in the speech_generation module
# recognize_speech() is the function in the speech_recognition module
# first_classifier() is the function in the nlu_one module
# second_classifier() is the function in the nlu_two module
global state_initial, features_dict
#generate_speech (" Hello. I'm your shoe shopping assistant. How can i help you", is_final = "False")
generate_speech(features_dict, "initial", "True")
while (state_initial == False):
statement = recognize_speech()
first_nlu_dict = first_classifier(statement, state="initial")
if (first_nlu_dict["info_initial_response"] != "empty"):
features_dict = first_nlu_dict
if (features_dict["info_initial_response"] != "empty"):
state_initial = True
else:
generate_speech(features_dict, "initial", first_nlu_dict)
def fetch_final_statement():
# generate_speech() is the function in the speech_generation module
# recognize_speech() is the function in the speech recognition module
# first_classifier() is the function in the nlu_one module
# second_classifier() is the function in the nlu_two module
global state_color, state_category, state_cost, state_final, positive_response_list, features_dict
generate_speech(features_dict, "final", "True")
while (state_final == False):
statement = recognize_speech()
first_nlu_dict = first_classifier(statement, "final")
if (first_nlu_dict["info_final_response"] == "yes"):
features_dict["info_final_response"] = first_nlu_dict[
"info_final_response"]
state_final = True
elif (first_nlu_dict["info_final_response"] == "no"):
state_category = False
state_color = False
state_cost = False
features_dict["info_color"] = "empty"
features_dict["info_category"] = "empty"
features_dict["info_cost"] = "empty"
fetch_info_category()
fetch_info_color()
fetch_info_cost()
generate_speech(features_dict, "final", "True")
else:
generate_speech(features_dict, "final", "True")
def fetch_info_cost():
# generate_speech() is the function in the speech_generation module
# recognize_speech() is the function in the speech recognition module
# first_classifier() is the function in the nlu_one module
# second_classifier() is the function in the nlu_two module
global state_cost, cost_list, features_dict
if (features_dict["info_cost"] != "empty"):
state_cost = True
else:
generate_speech(features_dict, "cost", "True")
while (state_cost == False):
statement = recognize_speech()
first_nlu_dict = first_classifier(statement, "cost")
if (first_nlu_dict["info_cost"] != "empty"):
features_dict["info_cost"] = first_nlu_dict["info_cost"]
if (features_dict["info_cost"] != "empty"):
state_cost = True
else:
generate_speech(features_dict, "cost", first_nlu_dict)
def fetch_results_from_db():
global features_dict
generate_speech(features_dict, "final", "empty")