def __init__(self, input_device_index: int = None):
"""Initiates Porcupine object for hot word detection.
Args:
input_device_index: Index of Input Device to use.
See Also:
- Instantiates an instance of Porcupine object and monitors audio stream for occurrences of keywords.
- A higher sensitivity results in fewer misses at the cost of increasing the false alarm rate.
- sensitivity: Tolerance/Sensitivity level. Takes argument or env var ``sensitivity`` or defaults to ``0.5``
References:
- `Audio Overflow <https://people.csail.mit.edu/hubert/pyaudio/docs/#pyaudio.Stream.read>`__ handling.
"""
logger.info(f"Initiating hot-word detector with sensitivity: {env.sensitivity}")
keyword_paths = [pvporcupine.KEYWORD_PATHS[x] for x in [pathlib.PurePath(__file__).stem]]
self.input_device_index = input_device_index
self.recorded_frames = []
self.py_audio = PyAudio()
self.detector = pvporcupine.create(
library_path=pvporcupine.LIBRARY_PATH,
model_path=pvporcupine.MODEL_PATH,
keyword_paths=keyword_paths,
sensitivities=[env.sensitivity]
)
self.audio_stream = None
def run(self):
ppn = None
recorder = None
try:
ppn = pvporcupine.create(access_key=self._access_key,
keywords=KEYWORDS,
sensitivities=[0.75] * len(KEYWORDS))
recorder = PvRecorder(device_index=self._device_index,
frame_length=ppn.frame_length)
recorder.start()
self._is_ready = True
while not self._stop:
pcm = recorder.read()
keyword_index = ppn.process(pcm)
if keyword_index >= 0:
self._keyword_var.set(KEYWORDS[keyword_index])
print(self._keyword_var.get())
finally:
if recorder is not None:
recorder.delete()
if ppn is not None:
ppn.delete()
self._is_stopped = True
def wake():
handle = pvporcupine.create(keywords=['bumblebee'], sensitivities=[0.1])
pa = pyaudio.PyAudio()
audio_stream = pa.open(rate=handle.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=handle.frame_length)
while True:
pcm = audio_stream.read(handle.frame_length)
pcm = struct.unpack_from("h" * handle.frame_length, pcm)
if handle.process(pcm):
# 回答“我在”
q_speak.put_nowait("我在")
try:
asr_txt = one_asr()
# asr_txt = ASR_WAKE_WORD
q_hmi_you.put_nowait(asr_txt)
# 意图分析
intent_txt = intent_for_send(asr_txt)
print(f'意图是：{intent_txt}')
q_hmi_sva.put_nowait(intent_txt)
if intent_txt is None:
# 回答“想好说什么再喊我”
q_speak.put_nowait("想好说什么再喊我")
else:
# 回答“好的”
q_speak.put_nowait("好的")
q_opc.put_nowait(intent_txt)
except sr.WaitTimeoutError:
# 回答“没别的事，我休息一下”
q_speak.put_nowait('没别的事，我休息一下')
def run(self, sentensivity):
porcupine = None
try:
keywords = ["jarvis"]
porcupine = pvporcupine.create(keywords=keywords,
sensitivities=[sentensivity])
pa = pyaudio.PyAudio()
audio_stream = pa.open(rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length)
logging.info('\nListening {%s}' % keywords)
while not self.stopped:
pcm = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
keyword_index = porcupine.process(pcm)
if keyword_index >= 0 and not self.recording:
self.recording = True
logging.info(
f'[ACTION] Detected {keywords[keyword_index]} at '
f'{datetime.now().hour}:{datetime.now().minute}')
self.recognize_input()
except MemoryError:
porcupine.delete()
self.start(self.sentensivity)
except:
logging.error(f"[ERROR] {traceback.print_exc()}")
def is_wake_up_word_said(input_device_index=13,
sensitivity=0.5,
keyword="hey pico",
timeout=10):
keyword_file_path = [pvporcupine.KEYWORD_FILE_PATHS[keyword]]
num_keywords = len(keyword_file_path)
porcupine = pvporcupine.create(library_path=pvporcupine.LIBRARY_PATH,
model_file_path=pvporcupine.MODEL_FILE_PATH,
keyword_file_paths=keyword_file_path,
sensitivities=[sensitivity] * num_keywords)
pa = pyaudio.PyAudio()
audio_stream = pa.open(rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length,
input_device_index=input_device_index)
start = time()
keyword_said = False
while not keyword_said and time() - start < timeout:
pcm = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
if porcupine.process(pcm):
keyword_said = True
audio_stream.close()
porcupine.delete()
return keyword_said
def __init__(self, sensitivity):
super(PorcupineDemo, self).__init__()
self._keywords = list(KEYWORDS_COLOR.keys())
self._porcupine = pvporcupine.create(keywords=self._keywords,
sensitivities=[sensitivity] *
len(KEYWORDS_COLOR))
def __init__(self, key_phrase="hey mycroft", config=None, lang="en-us"):
super().__init__(key_phrase, config, lang)
keyword_file_paths = [
expanduser(x.strip()) for x in self.config.get(
"keyword_file_path", "hey_mycroft.ppn").split(',')
]
sensitivities = self.config.get("sensitivities", 0.5)
access_key = self.config.get("access_key", None)
try:
import pvporcupine
from pvporcupine.util import (pv_library_path, pv_model_path)
except ImportError as err:
raise Exception(
"Python bindings for Porcupine not found. "
"Please run \"mycroft-pip install pvporcupine\"") from err
if isinstance(sensitivities, float):
sensitivities = [sensitivities] * len(keyword_file_paths)
else:
sensitivities = [float(x) for x in sensitivities.split(',')]
self.audio_buffer = []
self.has_found = False
self.num_keywords = len(keyword_file_paths)
LOG.info(
'Loading Porcupine using keyword path {} and sensitivities {}'.
format(keyword_file_paths, sensitivities))
self.porcupine = pvporcupine.create(access_key,
keyword_paths=keyword_file_paths,
sensitivities=sensitivities)
LOG.info('Loaded Porcupine')
def on_start(self):
self.running = True
print("\nStarting Hotword detection...")
self.keywords = ["caspar"]
keyword_paths = [pvporcupine.KEYWORD_PATHS[x] for x in self.keywords]
self.sensitivities = [0.5] * len(keyword_paths)
self.keywords = list()
for x in keyword_paths:
self.keywords.append(os.path.basename(x).replace('.ppn', '').split('_')[0])
self.porcupine = pvporcupine.create(
library_path=pvporcupine.LIBRARY_PATH,
model_path=pvporcupine.MODEL_PATH,
keyword_paths=keyword_paths,
sensitivities=self.sensitivities)
self.pa = pyaudio.PyAudio()
self.audio_stream = self.pa.open(
rate=self.porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=self.porcupine.frame_length,
input_device_index=None)
def listen(keywords=["blueberry"], sensitivity=0.5, action=None):
# define callback for action to take when wake words are detected
def _audio_callback(in_data, frame_count, time_info, status):
if frame_count >= porcupine.frame_length:
pcm = struct.unpack_from("h" * porcupine.frame_length, in_data)
result = porcupine.process(pcm)
index = result if len(keywords) > 1 else int(result) - 1
if index >= 0:
if action is None:
print("I heard {}!".format(keywords[index]))
else:
action(result)
return None, pyaudio.paContinue
porcupine = None
pa = None
audio_stream = None
try:
# initialize wake word detection
sensitivities = [float(sensitivity)] * len(keywords)
porcupine = pvporcupine.create(keywords=keywords,
sensitivities=sensitivities)
# create input audio stream
pa = pyaudio.PyAudio()
audio_stream = pa.open(
rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length,
input_device_index=None,
stream_callback=_audio_callback,
)
# start monitoring stream
audio_stream.start_stream()
print("Listening for keywords ...")
while True:
time.sleep(0.1)
except KeyboardInterrupt:
print("Stopping ...")
finally:
if audio_stream is not None:
audio_stream.stop_stream()
audio_stream.close()
if pa is not None:
pa.terminate()
# delete Porcupine last to avoid segfault in callback.
if porcupine is not None:
porcupine.delete()
def __init__(self, *args, wakewords='jarvis', **kwargs):
super().__init__(*args, **kwargs)
if type(wakewords) is not list:
wakewords = [wakewords]
self.wakewords = wakewords
self.handle = pvporcupine.create(keywords=wakewords)
def install(self, modules):
modules = super().install(modules)
self.__audio_recoder = modules['AudioRecorder']
self.__detect_handler = pvporcupine.create(
#library_path=self.__default_library_path(),
#model_path=self.__model_file_path(),
keyword_paths=[self.__keyword_file_path(self.__keyword_filename)],
sensitivities=[self.__sensitivity])
def __init__(self, access_key, device_index, sensitivity):
super(PorcupineDemo, self).__init__()
self._device_index = device_index
self._keywords = list(KEYWORDS_COLOR.keys())
self._porcupine = pvporcupine.create(access_key=access_key,
keywords=self._keywords,
sensitivities=[sensitivity] *
len(KEYWORDS_COLOR))
def __init__(self):
self._porcupine = pvporcupine.create(keywords=["picovoice"])
self._sound = pyaudio.PyAudio()
self._audio_stream = self._sound.open(
rate=self._porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=self._porcupine.frame_length)
def __init__(self):
# todo: hardcoded parameters
sensitivity = [0.5]
self.handle = pvporcupine.create(keywords=['jarvis'], sensitivities=sensitivity)
self.pa = pyaudio.PyAudio()
self.audio_stream = self.pa.open(
rate=self.handle.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=self.handle.frame_length)
def run(self):
keywords = list()
for x in self._keyword_paths:
keywords.append(
os.path.basename(x).replace('.ppn', '').split('_')[0])
porcupine = None
audio_stream_mic = None
try:
porcupine = pvporcupine.create(library_path=self._library_path,
model_path=self._model_path,
keyword_paths=self._keyword_paths,
sensitivities=self._sensitivities)
self._pa = pyaudio.PyAudio()
self.play_audio(WAV_READY_FILENAME)
audio_stream_mic = self._pa.open(
rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length)
print('Listening {')
for keyword, sensitivity in zip(keywords, self._sensitivities):
print(' %s (%.2f)' % (keyword, sensitivity))
print('}')
while True:
pcm = audio_stream_mic.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
result = porcupine.process(pcm)
if result >= 0:
print('[%s] Detected %s' %
(str(datetime.now()), keywords[result]))
self.play_audio(WAV_DETECTED_FILENAME)
except KeyboardInterrupt:
print('Stopping ...')
finally:
if porcupine is not None:
porcupine.delete()
if audio_stream_mic is not None:
audio_stream_mic.close()
if self._pa is not None:
self._pa.terminate()
def __init__(self):
super().__init__()
self._working = self.ThreadManager.newEvent('ListenForWakeword')
self._buffer = queue.Queue()
self._hotwordThread = None
try:
self._handler = pvporcupine.create(keywords=['porcupine', 'bumblebee', 'terminator', 'blueberry'])
with self.Commons.shutUpAlsaFFS():
self._audio = pyaudio.PyAudio()
except:
self._enabled = False
def picovoice():
try:
porcupine = pvporcupine.create(keywords=["picovoice", "blueberry"])
pa = pyaudio.PyAudio()
audio_stream = pa.open(rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length)
while True:
pcm = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
keyword_index = porcupine.process(pcm)
if keyword_index >= 0:
print("Hotword Detected")
audio_stream.close()
main()
print("Done")
except KeyboardInterrupt:
if porcupine is not None:
porcupine.delete()
print("deleting porc")
if audio_stream is not None:
audio_stream.close()
print("closing stream")
if pa is not None:
pa.terminate()
print("terminating pa")
exit(0)
finally:
if porcupine is not None:
porcupine.delete()
print("deleting porc")
if audio_stream is not None:
audio_stream.close()
print("closing stream")
if pa is not None:
pa.terminate()
print("terminating pa")
picovoice()
def main(self):
print("ready")
self.porcupine = None
pa = None
audio_stream = None
self.porcupine = pvporcupine.create(keywords=["jarvis"])
pa = pyaudio.PyAudio()
audio_stream = pa.open(rate=self.porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=self.porcupine.frame_length)
while True:
try:
pcm = audio_stream.read(self.porcupine.frame_length)
pcm = struct.unpack_from("h" * self.porcupine.frame_length,
pcm)
except:
audio_stream = pa.open(
rate=self.porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=self.porcupine.frame_length)
keyword_index = self.porcupine.process(pcm)
if keyword_index >= 0:
print("Hotword Detected")
try: #Tries terminating an action if it exists
action.terminate()
except:
pass
if audio_stream is not None:
audio_stream.close()
said = speak_listen.listen() #Listens for user input
print(said)
#action = multiprocessing.Process(target=
self.reply(said)
def __init__(self,
decoder_model,
resource=RESOURCE_FILE,
sensitivity=0.75,
audio_gain=1,
continue_recording=False,
output_dir=".",
delete_active_recording=False):
self.is_running = False
self.is_interrupted = False
self.is_recording = False
self.is_terminated = False
self._start_recording_callback = None
self._continue_recording_callback = None
self._stop_recording_callback = None
# Setup Porcupine
self.detector = pvporcupine.create(keywords=['alexa'],
sensitivities=[sensitivity])
# create detector buffer
self.detector_buffer = DetectorRingBuffer(self.detector.sample_rate *
5)
self.backward_buffer = None
# connect to the PyAudio stream
self.audio = pyaudio.PyAudio()
self.stream_in = self.audio.open(
input=True,
output=False,
format=pyaudio.paInt16,
channels=1,
rate=self.detector.sample_rate,
frames_per_buffer=self.detector.frame_length,
stream_callback=self._audio_callback)
# listen to interrupots
signal.signal(signal.SIGINT, self.stop)
self._enable_continue_recording = continue_recording
self._output_dir = output_dir
self._delete_active_recording = delete_active_recording
Log.debug(self._tag, "AudioHandler created")
def sense(self):
keywords = ["caspar"]
keyword_paths = [pvporcupine.KEYWORD_PATHS[x] for x in keywords]
sensitivities = [0.5] * len(keyword_paths)
keywords = list()
for x in keyword_paths:
keywords.append(os.path.basename(x).replace('.ppn', '').split('_')[0])
porcupine = pvporcupine.create(
library_path=pvporcupine.LIBRARY_PATH,
model_path=pvporcupine.MODEL_PATH,
keyword_paths=keyword_paths,
sensitivities=sensitivities)
pa = pyaudio.PyAudio()
audio_stream = pa.open(
rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length,
input_device_index=None)
print('\nListening {')
for keyword, sensitivity in zip(keywords, sensitivities):
print(' %s (%.2f)' % (keyword, sensitivity))
print('}')
while self.running:
pcm = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
result = porcupine.process(pcm)
if result >= 0:
print('[%s] Detected %s' % (str(datetime.now()), keywords[result]))
self.assert_belief(HOTWORD_DETECTED("ON"))
self.running = False
break
audio_stream.close()
pa.terminate()
porcupine.delete()
def esperaSaludo(): # añadir un temporizador que dado un tiempo maximo se salga con resultado de error
print("entra en esperaSaludo")
porcupine = None
pa = None
audio_stream = None
try:
porcupine = pvporcupine.create(keywords=['terminator'], sensitivities=[1.0])
pa = pyaudio.PyAudio()
audio_stream = pa.open(
rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length,
input_device_index=11)
print("Microfono listo")
while True:
pcm = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
keyword_index = porcupine.process(pcm)
if keyword_index >= 0:
print("DETECTADA!")
# pa.close()
break
finally:
if porcupine is not None:
porcupine.delete()
if audio_stream is not None:
audio_stream.close()
if pa is not None:
pa.terminate()
print("sale de esperaSaludo")
def _run(input_audio_file_path, library_path, model_file_path,
keyword_file_paths, sensitivity):
"""
Monitors an input audio file for occurrences of keywords for which keyword files are provided and prints their
occurrence time (in seconds from start of file).
:param input_audio_file_path: Absolute path to input audio file. The file should have a sample rate of 16000 and
be single-channel.
:param library_path: Absolute path to Porcupine's dynamic library.
:param model_file_path: Absolute path to the model parameter file.
:param keyword_file_paths: List of absolute paths to keyword files.
:param sensitivity: Sensitivity parameter. For more information refer to 'include/pv_porcupine.h'. It uses the
same sensitivity value for all keywords.
:return:
"""
num_keywords = len(keyword_file_paths)
porcupine = pvporcupine.create(library_path=library_path,
model_file_path=model_file_path,
keyword_file_paths=keyword_file_paths,
sensitivities=[sensitivity] * num_keywords)
def _frame_index_to_sec(frame_index):
return float(frame_index * porcupine.frame_length) / float(
porcupine.sample_rate)
audio, sample_rate = soundfile.read(input_audio_file_path, dtype='int16')
assert sample_rate == porcupine.sample_rate
num_frames = len(audio) // porcupine.frame_length
for i in range(num_frames):
frame = audio[i * porcupine.frame_length:(i + 1) *
porcupine.frame_length]
result = porcupine.process(frame)
if num_keywords == 1 and result:
print('detected keyword at time %f' % _frame_index_to_sec(i))
elif num_keywords > 1 and result >= 0:
print('detected keyword index %d at time %f' %
(result, _frame_index_to_sec(i)))
porcupine.delete()
def setup_voice_control():
try:
global porcupine
global pa
global audio_stream
porcupine = pvporcupine.create(keyword_paths=[
'wake_word\\pause_game_windows_3_30_2021_v1.9.0\\pause_game_windows_2021-03-30-utc_v1_9_0.ppn',
'wake_word\\play_game_windows_3_30_2021_v1.9.0\\play_game_windows_2021-03-30-utc_v1_9_0.ppn'
],
keywords=["blueberry", "grapefruit"])
pa = pyaudio.PyAudio()
print("loading complete")
audio_stream = pa.open(rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length)
return True
except Exception as e:
return False
def __init__(self, parent, keywords, user):
self.parent = parent
self.user = user
self.channel = parent.client.channel
self.pcp = create(keywords=keywords, sensitivities=[0.5] * len(keywords))
self.unpacker = Struct(f'{self.pcp.frame_length}h')
self.welcome_response = None
self.wuw_input = asyncio.Queue()
self.input_queue = self.wuw_input
self.what = parent.what
self.that = parent.that
self.ticktock = parent.ticktock
self.keywords = parent.keywords
self.play = parent.play
self.play_loop = parent.play_loop
self.play_stream = parent.play_stream
self.play_interruptible = parent.play_interruptible
self.say = parent.say
self.listen_task = BackgroundTask()
self.listen_task.start(self.listen_loop())
logger.info(f"Started {self!r}")
def run(self):
porcupine = py_audio_instance = audio_stream = None
try:
porcupine = pvporcupine.create(
keyword_paths=[
self.keyword_directory + "/" + f
for f in listdir(self.keyword_directory)
],
sensitivities=[self.sensitivity] *
len(listdir(self.keyword_directory)))
py_audio_instance = pyaudio.PyAudio()
audio_stream = py_audio_instance.open(
rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length,
input_device_index=self.input_device_index)
print("Listening for keyword.. ")
while True:
audio_frame = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length,
audio_frame)
if porcupine.process(pcm) >= 0:
self.run_func()
print("Listening for keyword.. ")
except KeyboardInterrupt:
print("Stopping ...")
finally:
if porcupine is not None:
porcupine.delete()
if audio_stream is not None:
audio_stream.close()
if py_audio_instance is not None:
py_audio_instance.terminate()
def __init__(self,
pv_model='./hey_diego_linux_2021-05-23-utc_v1_9_0.ppn',
speech_url='http://127.0.0.1:5000/speech',
status_url='http://127.0.0.1:5000/status',
nlp_url='http://127.0.0.1:5000/nlp'):
self.handle = pvporcupine.create(keyword_paths=[pv_model])
# Hey computer for the time being
#self.handle = pvporcupine.create(keywords=['computer'])
# Need to update this with an actual address
self.url = speech_url
self.status_url = status_url
self.nlp_url = nlp_url
self.pa = pyaudio.PyAudio()
self.audio_stream = self.pa.open(
rate=self.handle.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=self.handle.frame_length)
# Download dependencies
self.synthesizer = torch.hub.load('coqui-ai/TTS:dev',
'tts',
source='github')
def run(self):
"""
Creates an input audio stream, instantiates an instance of Porcupine object, and monitors the audio stream for
occurrences of the wake word(s). It prints the time of detection for each occurrence and the wake word.
"""
keywords = list()
for x in self._keyword_paths:
keywords.append(
os.path.basename(x).replace('.ppn', '').split('_')[0])
porcupine = None
try:
porcupine = pvporcupine.create(
library_path=pvporcupine.LIBRARY_PATH,
model_path=pvporcupine.MODEL_PATH,
keyword_paths=self._keyword_paths,
sensitivities=self._sensitivities)
my_log.debug(f"listening on keywords {keywords}")
with MicrophoneStream(self._audio_interface, porcupine.sample_rate,
porcupine.frame_length) as stream:
audio_generator = stream.generator()
for x in audio_generator:
if self.should_stop:
raise SystemExit("should_stop")
pcm = struct.unpack_from("h" * porcupine.frame_length, x)
result = porcupine.process(pcm)
if result >= 0:
my_log.debug(f"Detected {keywords[result]}")
porcupine_heard(keywords[result])
except Exception as e:
if type(e) != SystemExit:
my_log.exception(e)
finally:
if porcupine is not None:
porcupine.delete()
def wake_word():
porcupine = None
pa = None
audio_stream = None
try:
porcupine = pvporcupine.create(keywords=["blueberry"])
pa = pyaudio.PyAudio()
audio_stream = pa.open(rate=porcupine.sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=porcupine.frame_length)
while True:
pcm = audio_stream.read(porcupine.frame_length)
pcm = struct.unpack_from("h" * porcupine.frame_length, pcm)
keyword_index = porcupine.process(pcm)
if keyword_index >= 0:
print("Hotword Detected")
wake_word_detected = True
break
else:
print('not detected')
finally:
if porcupine is not None:
porcupine.delete()
if audio_stream is not None:
audio_stream.close()
if pa is not None:
pa.terminate()
def porcupine_wait_for_hotword(self, source, kywds, timeout=None):
self._waiting_for_hotword_callback()
# porcupine stuff
num_keywords = len(kywds)
porcupine = pvporcupine.create(keywords=kywds)
print(kywds)
elapsed_time = 0
seconds_per_buffer = float(source.CHUNK) / source.SAMPLE_RATE
resampling_state = None
# buffers capable of holding 5 seconds of original audio
five_seconds_buffer_count = int(math.ceil(5 / seconds_per_buffer))
# buffers capable of holding 0.5 seconds of resampled audio
half_second_buffer_count = int(math.ceil(0.5 / seconds_per_buffer))
frames = collections.deque(maxlen=five_seconds_buffer_count)
while True:
elapsed_time += seconds_per_buffer
if timeout and elapsed_time > timeout:
raise WaitTimeoutError(
"listening timed out while waiting for hotword to be said")
buffer = source.stream.read(source.CHUNK)
if len(buffer) == 0: break # reached end of the stream
frames.append(buffer)
pcm = struct.unpack_from("h" * porcupine.frame_length, buffer)
porcupine_result = porcupine.process(pcm)
if num_keywords == 1 and porcupine_result:
break
elif num_keywords > 1 and porcupine_result >= 0:
break
return b"".join(frames), elapsed_time
import pyaudio
import pvporcupine
from gtts import gTTS
from logmmse import logmmse_from_file
from mpyg321.mpyg321 import MPyg321Player
from responder import Responder
KEYWORDS = ["jarvis", "bumblebee"]
rp = Responder()
pa = pyaudio.PyAudio()
pl = MPyg321Player()
ai = wit.Wit(os.getenv("WITAI_TOKEN"))
porcupine = pvporcupine.create(keywords=KEYWORDS)
sample_rate = porcupine.sample_rate
frames_per_buffer = porcupine.frame_length
DURATION = 4.5
audio_stream = pa.open(
rate=sample_rate,
channels=1,
format=pyaudio.paInt16,
input=True,
frames_per_buffer=frames_per_buffer,
)
def get_command_recording():
