def loop_test(self):
if self.cmd:
print_debug('act | performing action \'%s\'...\n' % ACT2STR[int(self.cmd)])
# the 'result' variable is currently not being used
# but it can be used later to return the action performing status
self.result = True
self.cmd = ''
return
def loop_test(self):
if self.cmd:
print_debug('act | performing action \'%s\'...\n' %
ACT2STR[int(self.cmd)])
# the 'result' variable is currently not being used
# but it can be used later to return the action performing status
self.result = True
self.cmd = ''
return
def setup(self):
self.audio = pyaudio.PyAudio()
self.stream = self.audio.open(format=FORMAT,
channels=CHANNELS,
rate=RATE,
frames_per_buffer=CHUNK,
input_device_index=DEVICE,
input=True)
print_debug('asr | listening...\n')
return
def setup(self):
self.audio = pyaudio.PyAudio()
self.stream = self.audio.open(format=FORMAT,
channels=CHANNELS,
rate=RATE,
frames_per_buffer=CHUNK,
input_device_index=DEVICE,
input=True)
print_debug('asr | listening...\n')
return
def loop(self):
if self.cmd:
print_debug('act | performing action ...\n')
# shell_cmd = ACTION_SCRIPT+' '+self.cmd
# os.system(shell_cmd)
call([ACTION_SCRIPT, self.cmd])
# the 'result' variable is currently not being used
# but it can be used later to return the action performing status
self.result = True
self.cmd = ''
return
def loop(self):
if self.cmd:
print_debug('act | performing action ...\n')
# shell_cmd = ACTION_SCRIPT+' '+self.cmd
# os.system(shell_cmd)
call([ACTION_SCRIPT, self.cmd])
# the 'result' variable is currently not being used
# but it can be used later to return the action performing status
self.result = True
self.cmd = ''
return
def dm_process(pipe):
# initialize dialog manager
dm = DialogManager()
print '=> dialog manager started'
# main loop
while True:
if pipe.poll():
cmd = pipe.recv()
print_debug('controller | %s\n' % cmd)
ret = dm.handle(cmd)
if not ret: break
dm.loop()
pipe.close()
print '=> dialog manager closed'
return
def start_module(self, mod_id):
if mod_id == MODULE.ALL:
self.start_all()
return
if not self.processes[mod_id]:
parent, child = Pipe()
self.pipes[mod_id] = parent
# self.processes[mid] = Queue()
try:
self.processes[mod_id] = Process(target=PROCESS_FN[mod_id], args=(child,))
self.processes[mod_id].start()
except Exception as e:
print_debug('manager | unable to start {0} ({1})\n'.format(self.id2mod[mod_id],e))
else:
print_debug('manager | %s already started\n' % self.id2mod[mod_id])
return
def terminate_module(self, mod_id):
if mod_id==MODULE.ALL:
self.terminate_all()
return
if self.processes[mod_id]:
if self.processes[mod_id].is_alive():
self.pipes[mod_id].send('exit')
self.processes[mod_id].join()
else:
print_debug('manager | %s terminated\n' % self.id2mod[mod_id])
self.processes[mod_id] = None
if self.pipes[mod_id]:
self.pipes[mod_id].close()
self.pipes[mod_id] = None
else:
print_debug('manager | %s already terminated\n' % self.id2mod[mod_id])
return
def loop(self):
if self.text:
# self.http_para['text'] = self.text
text = '+'.join(self.text.split())
with open(TTS_OUTPUT_WAVE, 'wb') as outfile:
# response = requests.get(TTS_URL, headers=self.http_header, data=self.http_para, stream=True)
url = TTS_URL+'&text='+text
response = requests.get(url, headers=self.http_header, stream=True)
if not response.ok:
# Something went wrong
print_debug('tts | fail to download wave file ({0})\n'.format(response.status_code))
else:
for block in response.iter_content(1024):
outfile.write(block)
self.result = True
# print_debug('tts | wave file downloaded\n')
self.text = ''
return
def process(self):
# suspend mic
self.stream.stop_stream()
if self.utter<=UTTERANCE_THRESHOLD:
print_debug('asr | (temporal noise)\n')
else:
print_debug('asr | processing...\n')
# (deprecated) for processing ring buffer that could be not full
# if self.rb_full:
# _data = self.silence[self.p_rb:] + self.silence[:self.p_rb] + self.utterance
# else:
# _data = self.silence[:self.p_rb] + self.utterance
# ring better is guaranteed to be full
data = self.silence[self.p_rb:] + self.silence[:self.p_rb] + self.utterance
# save as wave file
self.save_speech(data)
# submit to GSR
self.transcribe()
print_debug('asr | listening...\n')
# resume mic
self.reset()
self.stream.start_stream()
return
def handle(self, command):
# high priority command
if command == 'exit':
self.terminate_all()
return False
# extract module, command, message
tmp = command.split(':')
for _ in xrange(len(tmp),3): tmp.append(None)
mod,cmd,msg = tmp[0],tmp[1],tmp[2]
# check module validity
if mod not in self.mod2id:
print_debug('manager | unable to recognize module: %s\n' % command)
return True
else: mod = self.mod2id[mod]
# map command into function
if cmd=='start':
self.start_module(mod)
elif cmd=='exit':
self.terminate_module(mod)
elif cmd=='msg':
if not msg: print_debug('manager | empty message: %s\n' % command)
else: self.send_msg(mod,msg)
else:
print_debug('manager | unrecognized command: %s\n' % command)
return True
def process(self):
# suspend mic
self.stream.stop_stream()
if self.utter <= UTTERANCE_THRESHOLD:
print_debug('asr | (temporal noise)\n')
else:
print_debug('asr | processing...\n')
# (deprecated) for processing ring buffer that could be not full
# if self.rb_full:
# _data = self.silence[self.p_rb:] + self.silence[:self.p_rb] + self.utterance
# else:
# _data = self.silence[:self.p_rb] + self.utterance
# ring better is guaranteed to be full
data = self.silence[
self.p_rb:] + self.silence[:self.p_rb] + self.utterance
# save as wave file
self.save_speech(data)
# submit to GSR
self.transcribe()
print_debug('asr | listening...\n')
# resume mic
self.reset()
self.stream.start_stream()
return
def loop(self):
# record new data chunk from mic
try:
data = self.stream.read(CHUNK)
except IOError:
return
# calculate amplitude based on root mean square
amp = audioop.rms(data, DEPTH / 8)
# display amplitude bar
bar_len = min(MAX_LINE, amp / SLOPE)
print_debug('[' + '|' * bar_len + ' ' * (MAX_LINE - bar_len) +
'] rms:' + str(amp))
# determine silent or not based on threshold
silent = amp < SILENT_THRESHOLD
if silent and not self.recording:
# append data to ring buffer
self.silence[self.p_rb] = data
self.p_rb = (self.p_rb + 1) % SIL_BEG
if not self.p_rb: self.rb_full = True
else:
# ensure 1 sec of beginning silence for the first utterance
if not self.rb_full: return
# append data to utterance
self.utterance.append(data)
if not self.recording:
# implies that it's not silent
self.utter += 1
self.recording = True
elif silent:
# implies that it's recording
self.p_sil += 1
if self.p_sil == SIL_END:
# utterance collected, process!
self.process()
else:
# recording and not silent
self.utter += 1
self.p_sil = 0
return
def loop(self):
if self.text:
# self.http_para['text'] = self.text
text = '+'.join(self.text.split())
with open(TTS_OUTPUT_WAVE, 'wb') as outfile:
# response = requests.get(TTS_URL, headers=self.http_header, data=self.http_para, stream=True)
url = TTS_URL + '&text=' + text
response = requests.get(url,
headers=self.http_header,
stream=True)
if not response.ok:
# Something went wrong
print_debug(
'tts | fail to download wave file ({0})\n'.format(
response.status_code))
else:
for block in response.iter_content(1024):
outfile.write(block)
self.result = True
# print_debug('tts | wave file downloaded\n')
self.text = ''
return
def loop(self):
# record new data chunk from mic
try:
data = self.stream.read(CHUNK)
except IOError:
return
# calculate amplitude based on root mean square
amp = audioop.rms(data, DEPTH/8)
# display amplitude bar
bar_len = min(MAX_LINE, amp/SLOPE)
print_debug('['+'|'*bar_len+' '*(MAX_LINE-bar_len)+'] rms:'+str(amp))
# determine silent or not based on threshold
silent = amp < SILENT_THRESHOLD
if silent and not self.recording:
# append data to ring buffer
self.silence[self.p_rb] = data
self.p_rb = (self.p_rb + 1) % SIL_BEG
if not self.p_rb: self.rb_full = True
else:
# ensure 1 sec of beginning silence for the first utterance
if not self.rb_full: return
# append data to utterance
self.utterance.append(data)
if not self.recording:
# implies that it's not silent
self.utter += 1
self.recording = True
elif silent:
# implies that it's recording
self.p_sil += 1
if self.p_sil == SIL_END:
# utterance collected, process!
self.process()
else:
# recording and not silent
self.utter += 1
self.p_sil = 0
return
def asr_process(pipe):
print 'asr | process started'
gsr = GSR()
# setup gsr
gsr.setup()
while True:
# process input command if any
if pipe.poll():
cmd = pipe.recv()
print_debug('asr | received: %s\n' % cmd)
if cmd=='exit': break
# loop gsr
# gsr.loop_test()
gsr.loop()
# send recognized text if any
if gsr.text:
pipe.send(gsr.text)
if gsr.text=='exit': break
gsr.text = ''
# clean up gsr
gsr.clean_up()
pipe.close()
print 'asr | process terminated'
return
def asr_process(pipe):
print 'asr | process started'
gsr = GSR()
# setup gsr
gsr.setup()
while True:
# process input command if any
if pipe.poll():
cmd = pipe.recv()
print_debug('asr | received: %s\n' % cmd)
if cmd == 'exit': break
# loop gsr
# gsr.loop_test()
gsr.loop()
# send recognized text if any
if gsr.text:
pipe.send(gsr.text)
if gsr.text == 'exit': break
gsr.text = ''
# clean up gsr
gsr.clean_up()
pipe.close()
print 'asr | process terminated'
return
def slu_process(pipe):
slu = SLU()
print_debug('slu | process started\n')
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text=='exit': break
slu.text = text
slu.loop()
# send result back to dialog manager
if slu.result:
pipe.send(slu.result)
print_debug('slu | %s | %s\n' % (slu.result['mod'],slu.result['data']))
slu.result = None
pipe.close()
print_debug('slu | process terminated\n')
return
def slu_process(pipe):
slu = SLU()
print_debug('slu | process started\n')
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
slu.text = text
slu.loop()
# send result back to dialog manager
if slu.result:
pipe.send(slu.result)
print_debug('slu | %s | %s\n' %
(slu.result['mod'], slu.result['data']))
slu.result = None
pipe.close()
print_debug('slu | process terminated\n')
return
def act_process(pipe):
print_debug('act | process started\n')
act = ACT()
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
act.cmd = text
act.loop()
# feed back if necessary
if act.result:
print_debug('act | action done')
# pipe.send('some kind of indicator')
act.result = False
# less CPU occupancy
time.sleep(0.01)
pipe.close()
print_debug('act | process terminated\n')
return
def act_process(pipe):
print_debug('act | process started\n')
act = ACT()
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
act.cmd = text
act.loop()
# feed back if necessary
if act.result:
print_debug('act | action done')
# pipe.send('some kind of indicator')
act.result = False
# less CPU occupancy
time.sleep(0.01)
pipe.close()
print_debug('act | process terminated\n')
return
def transcribe(self):
# wave_file = os.path.join(path.dirname(path.realpath(__file__)), WAVE_OUTPUT_FILENAME)
wave_file = os.path.join(ASR_OUTPUT_WAVE)
recognizer = sr.Recognizer()
with sr.WavFile(wave_file) as source:
_data = recognizer.record(source) # read the entire WAV file
# recognize speech using Google Speech Recognition
try:
self.text = recognizer.recognize_google(_data)
# print recognizer.recognize_google(_data, show_all=True)
except sr.UnknownValueError:
# print(" | error: could not understand audio (empty input?)")
print_debug('asr | (empty)\n')
self.text = ''
return
except sr.RequestError as e:
print_debug('asr | error: could not request results from service; {0}\n'.format(e))
self.clean_up()
exit()
print_debug('asr | speech: %s\n' % self.text)
return
def tts_process(pipe):
print_debug('tts | process started\n')
tts = TTS()
tts.setup()
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text=='exit': break
tts.text = text
tts.loop()
# play the returned wave only once
if tts.result:
# pipe.send('something')
print_debug('tts | playing back...\n')
tts.play()
tts.result = False
# less CPU occupancy
time.sleep(0.01)
tts.clean_up()
pipe.close()
print_debug('tts | process terminated\n')
return
def tts_process(pipe):
print_debug('tts | process started\n')
tts = TTS()
tts.setup()
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
tts.text = text
tts.loop()
# play the returned wave only once
if tts.result:
# pipe.send('something')
print_debug('tts | playing back...\n')
tts.play()
tts.result = False
# less CPU occupancy
time.sleep(0.01)
tts.clean_up()
pipe.close()
print_debug('tts | process terminated\n')
return
def transcribe(self):
# wave_file = os.path.join(path.dirname(path.realpath(__file__)), WAVE_OUTPUT_FILENAME)
wave_file = os.path.join(ASR_OUTPUT_WAVE)
recognizer = sr.Recognizer()
with sr.WavFile(wave_file) as source:
_data = recognizer.record(source) # read the entire WAV file
# recognize speech using Google Speech Recognition
try:
self.text = recognizer.recognize_google(_data)
# print recognizer.recognize_google(_data, show_all=True)
except sr.UnknownValueError:
# print(" | error: could not understand audio (empty input?)")
print_debug('asr | (empty)\n')
self.text = ''
return
except sr.RequestError as e:
print_debug(
'asr | error: could not request results from service; {0}\n'.
format(e))
self.clean_up()
exit()
print_debug('asr | speech: %s\n' % self.text)
return
def act_process(pipe):
print_debug('act | process started\n')
act = ACT()
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
act.cmd = text
act.loop()
# feed back if necessary
if act.result:
print_debug('act | action done')
# pipe.send('some kind of indicator')
act.result = False
# less CPU occupancy
time.sleep(0.01)
pipe.close()
print_debug('act | process terminated\n')
return
if __name__ == '__main__':
_act = ACT()
_act.cmd = '1'
_act.loop_test()
if _act.result:
print_debug('act | performing action \'%s\'...\n' % _act.result)
_act.result = ''
def act_process(pipe):
print_debug('act | process started\n')
act = ACT()
while True:
# process input command if any
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
act.cmd = text
act.loop()
# feed back if necessary
if act.result:
print_debug('act | action done')
# pipe.send('some kind of indicator')
act.result = False
# less CPU occupancy
time.sleep(0.01)
pipe.close()
print_debug('act | process terminated\n')
return
if __name__ == '__main__':
_act = ACT()
_act.cmd = '1'
_act.loop_test()
if _act.result:
print_debug('act | performing action \'%s\'...\n' % _act.result)
_act.result = ''
text = pipe.recv()
if text=='exit': break
tts.text = text
tts.loop()
# play the returned wave only once
if tts.result:
# pipe.send('something')
print_debug('tts | playing back...\n')
tts.play()
tts.result = False
# less CPU occupancy
time.sleep(0.01)
tts.clean_up()
pipe.close()
print_debug('tts | process terminated\n')
return
if __name__ == '__main__':
TTS_OUTPUT_WAVE = '../tmp/tts.wav'
API_AI_CREDENTIAL = '../configs/credential.json'
_tts = TTS()
_tts.setup()
_tts.text = 'it\'s 26 degree, with shower rain.'
_tts.loop()
if _tts.result:
print_debug('tts | playing back...\n')
_tts.play()
_tts.clean_up()
def load_hmm(self):
print_debug('slu | initializing recognizer...\n')
# set True to train new model and False to load from pre-trained
self.hmm_seq_recognizer = predefined_hmm(MODEL_PATH, False)
return
if __name__ == '__main__':
# make sure the controller is running
if not os.path.exists(NAMED_PIPE):
print '=> missing named pipe, please run the controller first'
exit()
# create dialog manager process
parent, child = Pipe()
dmp = Process(target=dm_process, args=(child, ))
dmp.start()
# main loop, receive commands from named pipeto and relay to dialog manager
while True:
# print('waiting...')
fifo = open(NAMED_PIPE, 'r')
# receive command from controller through named pipe
cmd = fifo.readline()
print_debug('controller | ' + cmd)
fifo.close()
# send command to dialog manager
parent.send(cmd)
if cmd == 'exit':
# wait for dialog manager to terminate
dmp.join()
# close parent pipe, child pipe will be close in child process
parent.close()
break
# leave time for controller to open the named pipe first
time.sleep(0.1)
if pipe.poll():
text = pipe.recv()
if text == 'exit': break
tts.text = text
tts.loop()
# play the returned wave only once
if tts.result:
# pipe.send('something')
print_debug('tts | playing back...\n')
tts.play()
tts.result = False
# less CPU occupancy
time.sleep(0.01)
tts.clean_up()
pipe.close()
print_debug('tts | process terminated\n')
return
if __name__ == '__main__':
TTS_OUTPUT_WAVE = '../tmp/tts.wav'
API_AI_CREDENTIAL = '../configs/credential.json'
_tts = TTS()
_tts.setup()
_tts.text = 'it\'s 26 degree, with shower rain.'
_tts.loop()
if _tts.result:
print_debug('tts | playing back...\n')
_tts.play()
_tts.clean_up()
if __name__ == '__main__':
# make sure the controller is running
if not os.path.exists(NAMED_PIPE):
print '=> missing named pipe, please run the controller first'
exit()
# create dialog manager process
parent,child = Pipe()
dmp = Process(target=dm_process, args=(child,))
dmp.start()
# main loop, receive commands from named pipeto and relay to dialog manager
while True:
# print('waiting...')
fifo = open(NAMED_PIPE, 'r')
# receive command from controller through named pipe
cmd = fifo.readline()
print_debug('controller | '+cmd)
fifo.close()
# send command to dialog manager
parent.send(cmd)
if cmd=='exit':
# wait for dialog manager to terminate
dmp.join()
# close parent pipe, child pipe will be close in child process
parent.close()
break
# leave time for controller to open the named pipe first
time.sleep(0.1)
def load_hmm(self):
print_debug('slu | initializing recognizer...\n')
# set True to train new model and False to load from pre-trained
self.hmm_seq_recognizer = predefined_hmm(MODEL_PATH, False)
return