def CognitiveSystem(Window, SpeechToNLPQueue):
# Create GUI signal objects
SpeechSignal = GUISignal()
SpeechSignal.signal.connect(Window.UpdateSpeechBox)
ConceptExtractionSignal = GUISignal()
ConceptExtractionSignal.signal.connect(Window.UpdateConceptExtractionBox)
# Initialize BT framework parameters
execfile("bt_parameters.py")
# Setup BT Framework
blackboard = Blackboard()
root = py_trees.composites.Sequence("Root_1")
IG = be.InformationGathering()
TC = be.TextCollection()
V = be.Vectorize()
PS = be.ProtocolSelector()
root.add_children([TC, IG, V, PS, be.protocols])
behaviour_tree = py_trees.trees.BehaviourTree(root)
behaviour_tree.add_pre_tick_handler(pre_tick_handler)
behaviour_tree.setup(15)
Concepts_Graph = dict()
SpeechText = ""
NLP_Items = []
Tick_Counter = 1
while True:
# Get queue item from the Speech-to-Text Module
received = SpeechToNLPQueue.get()
print("Received chunk")
if (received == 'Kill'):
print(
"Cognitive System Thread received Kill Signal. Killing Cognitive System Thread."
)
break
if (Window.reset == 1):
print(
"Cognitive System Thread Received reset signal. Killing Cognitive System Thread."
)
return
# If item received from queue is legitmate
else:
#sentsList = [received.transcript]
# Use online tool to find sentence boundaries
dummy12 = received.transcript
dummy12 = dummy12.replace('\r', '').replace('\n', '')
dummyP2 = dummy12.replace(' ', '%20')
dummyP3 = dummyP2.replace('\'', '%27')
dummyP = dummyP3.replace('&', '%26')
part1 = 'curl -d text=' + dummyP + ' http://bark.phon.ioc.ee/punctuator'
op = commands.getstatusoutput(part1)
output = op[1].rsplit('\n', 1)[1]
sentsList = textParse2.sent_tokenize(output) #final sentences
# Processes each chunk/sentence
PunctuatedAndHighlightedText = ""
for idx, item in enumerate(sentsList):
blackboard.text = [item]
behaviour_tree.tick_tock(sleep_ms=50,
number_of_iterations=1,
pre_tick_handler=None,
post_tick_handler=None)
pr, sv_s, s = TickResults(Window, NLP_Items)
PunctuatedAndHighlightedTextChunk = item
for sv in sv_s:
if (sv[5] == Tick_Counter
): # if new concept found in this tick
try:
i = re.search(
r'%s' % sv[3],
PunctuatedAndHighlightedTextChunk).start()
PunctuatedAndHighlightedTextChunk = str(
PunctuatedAndHighlightedTextChunk[:i] +
'<span style="background-color: #FFFF00">' +
PunctuatedAndHighlightedTextChunk[i:i +
len(sv[3])] +
'</span>' +
PunctuatedAndHighlightedTextChunk[i +
len(sv[3]):])
except Exception as e:
pass
PunctuatedAndHighlightedText += PunctuatedAndHighlightedTextChunk + " "
Tick_Counter += 1
if (Window.reset == 1):
print(
"Cognitive System Thread Received reset signal. Killing Cognitive System Thread."
)
return
PunctuatedAndHighlightedText = '<b>' + PunctuatedAndHighlightedText + '</b>'
SpeechSignal.signal.emit([
SpeechNLPItem(PunctuatedAndHighlightedText, received.isFinal,
received.confidence, received.numPrinted, 'NLP')
])
vt.pop(idx)
for idx, it in enumerate(vt):
temp = it.split('-')
vt[idx] = (temp[0], temp[1])
chunked_vt = list(np.array_split(vt, len(chunks)))
blackboard = Blackboard()
root = py_trees.composites.Sequence("Root_1")
IG = be.InformationGathering()
TC = be.TextCollection()
V = be.Vectorize()
PS = be.ProtocolSelector()
root.add_children([TC, IG, V, PS, be.protocols])
behaviour_tree = py_trees.trees.BehaviourTree(root)
behaviour_tree.add_pre_tick_handler(pre_tick_handler)
behaviour_tree.setup(15)
for idx, item in enumerate(chunks):
blackboard.text = [item]
blackboard.inC = list(chunked_vt[idx])
behaviour_tree.tick_tock(sleep_ms=50,
number_of_iterations=1,
pre_tick_handler=None,
post_tick_handler=None)
res = []
for key in blackboard.feedback:
if blackboard.feedback[key] > 0.1:
res.append((key, blackboard.feedback[key]))
temp_int.append(res)
print blackboard.candi[0]
print res
pred_int.append(temp_int)
