def main():
args = create_parser(usage).parse_args()
print('chunk_size: ', args.chunk_size)
def on_activation():
activate_notify()
if args.save_dir:
global chunk_num
nm = join(args.save_dir, args.save_prefix + session_id + '.' + str(chunk_num) + '.wav')
save_audio(nm, audio_buffer)
print()
print('Saved to ' + nm + '.')
chunk_num += 1
def on_prediction(conf):
print('!' if conf > 0.8 else '.', end='', flush=True)
listener = Listener(args.model, args.chunk_size)
audio_buffer = np.zeros(listener.pr.buffer_samples, dtype=float)
def get_prediction(chunk):
nonlocal audio_buffer
audio = buffer_to_audio(chunk)
audio_buffer = np.concatenate((audio_buffer[len(audio):], audio))
return listener.update(chunk)
engine = ListenerEngine(listener, args.chunk_size)
engine.get_prediction = get_prediction
runner = PreciseRunner(engine, args.threshold, on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
Event().wait() # Wait forever
def main():
args = create_parser(usage).parse_args()
sensitivity = 0.5
def on_activation():
activate_notify()
if args.save_dir:
global chunk_num
nm = join(
args.save_dir,
args.save_prefix + session_id + '.' + str(chunk_num) + '.wav')
save_audio(nm, audio_buffer)
print()
print('Saved to ' + nm + '.')
chunk_num += 1
def on_prediction(conf):
if args.light_mode:
print('!' if conf > 0.7 else '.', end='', flush=True)
else:
max_width = 80
width = min(get_terminal_size()[0], max_width)
units = int(round(conf * width))
bar = 'X' * units + '-' * (width - units)
cutoff = round((1.0 - sensitivity) * width)
print(bar[:cutoff] + bar[cutoff:].replace('X', 'x'))
listener = Listener(args.model, args.chunk_size)
audio_buffer = np.zeros(listener.pr.buffer_samples, dtype=float)
def get_prediction(chunk):
nonlocal audio_buffer
audio = buffer_to_audio(chunk)
audio_buffer = np.concatenate((audio_buffer[len(audio):], audio))
return listener.update(chunk)
engine = ListenerEngine(listener, args.chunk_size)
engine.get_prediction = get_prediction
runner = PreciseRunner(engine,
args.threshold,
sensitivity=sensitivity,
on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
Event().wait() # Wait forever
def __init__(self, connection, address):
self.address = address
self.connection = connection # type: socket.socket
self.stream = ReadWriteStream()
self.runner = PreciseRunner(
ListenerEngine(Listener(MODEL_NAME, CHUNK_SIZE), CHUNK_SIZE),
1, stream=self.stream, on_activation=self.on_activation,
on_prediction=self.on_prediction
)
self.runner.start()
def main():
rospy.init_node('wake_word_detection_node')
print("node is up")
def on_activation():
print("activate")
playsound(res_path + "/attention.wav")
try:
requests.get('http://www.google.com')
try:
response = stop_speech_perception_service(True)
print(response)
except rospy.ServiceException as exc:
print("Service did not process request: " + str(exc))
except requests.ConnectionError:
print("no internet")
speak_pub.publish(
"I'm sorry. I am not connected to the internet now and cannot answer"
)
set_emotion_service(state="SADNESS", timeout=5500, restore=True)
def on_prediction(conf):
print(".")
listener = Listener(res_path + "/stevie_10_06.pb", chunk_size)
audio_buffer = np.zeros(listener.pr.buffer_samples, dtype=float)
def get_prediction(chunk):
nonlocal audio_buffer
audio = buffer_to_audio(chunk)
audio_buffer = np.concatenate((audio_buffer[len(audio):], audio))
return listener.update(chunk)
engine = ListenerEngine(listener, chunk_size)
engine.get_prediction = get_prediction
runner = PreciseRunner(engine,
trigger_level=3,
sensitivity=0.5,
on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
print("spinning")
rospy.spin()
def main():
args = create_parser(usage).parse_args()
def on_activation():
activate_notify()
if args.save_dir:
global chunk_num
nm = join(
args.save_dir,
args.save_prefix + session_id + '.' + str(chunk_num) + '.wav')
save_audio(nm, audio_buffer)
print()
print('Saved to ' + nm + '.')
chunk_num += 1
def on_prediction(conf):
global detecting_flag
# print('!' if conf > 0.5 else '.', end='', flush=True)
if conf > 0.5:
detecting_flag = True
if conf < 0.5 and detecting_flag:
print(colored("Yeah! I'm Here.", 'green'))
detecting_flag = False
sunshine_model = './ok-sunshine.net'
listener = Listener(sunshine_model, args.chunk_size)
audio_buffer = np.zeros(listener.pr.buffer_samples, dtype=float)
def get_prediction(chunk):
nonlocal audio_buffer
audio = buffer_to_audio(chunk)
audio_buffer = np.concatenate((audio_buffer[len(audio):], audio))
return listener.update(chunk)
engine = ListenerEngine(listener, args.chunk_size)
engine.get_prediction = get_prediction
runner = PreciseRunner(engine,
args.threshold,
on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
Event().wait() # Wait forever
def __init__(self, args):
super().__init__(args)
self.listener = Listener(args.model, args.chunk_size)
self.audio_buffer = np.zeros(self.listener.pr.buffer_samples,
dtype=float)
self.engine = ListenerEngine(self.listener, args.chunk_size)
self.engine.get_prediction = self.get_prediction
self.runner = PreciseRunner(self.engine,
args.trigger_level,
sensitivity=args.sensitivity,
on_activation=self.on_activation,
on_prediction=self.on_prediction)
self.session_id, self.chunk_num = '%09d' % randint(0, 999999999), 0
def main():
args = create_parser(usage).parse_args()
def on_activation():
activate_notify()
# TODO: trigger VMSE
def on_prediction(conf):
if args.basic_mode:
print('!' if conf > 0.7 else '.', end='', flush=True)
else:
max_width = 80
width = min(get_terminal_size()[0], max_width)
units = int(round(conf * width))
bar = 'X' * units + '-' * (width - units)
cutoff = round((1.0 - args.sensitivity) * width)
print(bar[:cutoff] + bar[cutoff:].replace('X', 'x'))
listener = Listener(args.model, args.chunk_size)
audio_buffer = np.zeros(listener.pr.buffer_samples, dtype=float)
def get_prediction(chunk):
nonlocal audio_buffer
audio = buffer_to_audio(chunk)
audio_buffer = np.concatenate((audio_buffer[len(audio):], audio))
return listener.update(chunk)
engine = ListenerEngine(listener, args.chunk_size)
engine.get_prediction = get_prediction
runner = PreciseRunner(engine,
args.trigger_level,
sensitivity=args.sensitivity,
on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
Event().wait() # Wait forever
def main():
args = create_parser(usage).parse_args()
def on_activation():
Popen(['aplay', '-q', 'data/activate.wav'])
def on_prediction(conf):
print('!' if conf > 0.5 else '.', end='', flush=True)
runner = PreciseRunner(ListenerEngine(
PocketsphinxListener(args.key_phrase, args.dict_file, args.hmm_folder,
args.threshold, args.chunk_size)),
3,
on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
Event().wait() # Wait forever
def run(self):
def on_activation():
activate_notify()
def on_prediction(conf):
print('!' if conf > 0.5 else '.', end='', flush=True)
args = self.args
runner = PreciseRunner(ListenerEngine(
PocketsphinxListener(args.key_phrase, args.dict_file,
args.hmm_folder, args.threshold,
args.chunk_size)),
3,
on_activation=on_activation,
on_prediction=on_prediction)
runner.start()
Event().wait() # Wait forever