详解python的webrtc库实现语音端点检测

'''Requirements:+ pyaudio - `pip install pyaudio`+ py-webrtcvad - `pip install webrtcvad`'''import webrtcvadimport collectionsimport sysimport signalimport pyaudiofrom array import arrayfrom struct import packimport waveimport timeFORMAT = pyaudio.paInt16CHANNELS = 1RATE = 16000CHUNK_DURATION_MS = 30    # supports 10, 20 and 30 (ms)PADDING_DURATION_MS = 1500  # 1 sec jugementCHUNK_SIZE = int(RATE CHUNK_DURATION_MS / 1000) # chunk to readCHUNK_BYTES = CHUNK_SIZE 2 # 16bit = 2 bytes, PCMNUM_PADDING_CHUNKS = int(PADDING_DURATION_MS / CHUNK_DURATION_MS)# NUM_WINDOW_CHUNKS = int(240 / CHUNK_DURATION_MS)NUM_WINDOW_CHUNKS = int(400 / CHUNK_DURATION_MS) # 400 ms/ 30ms geNUM_WINDOW_CHUNKS_END = NUM_WINDOW_CHUNKS 2START_OFFSET = int(NUM_WINDOW_CHUNKS CHUNK_DURATION_MS 0.5 RATE)vad = webrtcvad.Vad(1)pa = pyaudio.PyAudio()stream = pa.open(format=FORMAT,         channels=CHANNELS,         rate=RATE,         input=True,         start=False,         # input_device_index=2,         frames_per_buffer=CHUNK_SIZE)got_a_sentence = Falseleave = Falsedef handle_int(sig, chunk):  global leave, got_a_sentence  leave = True  got_a_sentence = Truedef record_to_file(path, data, sample_width):  "Records from the microphone and outputs the resulting data to 'path'"  # sample_width, data = record()  data = pack('<' + ('h' len(data)), data)  wf = wave.open(path, 'wb')  wf.setnchannels(1)  wf.setsampwidth(sample_width)  wf.setframerate(RATE)  wf.writeframes(data)  wf.close()def normalize(snd_data):  "Average the volume out"  MAXIMUM = 32767 # 16384  times = float(MAXIMUM) / max(abs(i) for i in snd_data)  r = array('h')  for i in snd_data:    r.append(int(i times))  return rsignal.signal(signal.SIGINT, handle_int)while not leave:  ring_buffer = collections.deque(maxlen=NUM_PADDING_CHUNKS)  triggered = False  voiced_frames = []  ring_buffer_flags = [0] NUM_WINDOW_CHUNKS  ring_buffer_index = 0  ring_buffer_flags_end = [0] NUM_WINDOW_CHUNKS_END  ring_buffer_index_end = 0  buffer_in = ''  # WangS  raw_data = array('h')  index = 0  start_point = 0  StartTime = time.time()  print(" recording: ")  stream.start_stream()  while not got_a_sentence and not leave:    chunk = stream.read(CHUNK_SIZE)    # add WangS    raw_data.extend(array('h', chunk))    index += CHUNK_SIZE    TimeUse = time.time() - StartTime    active = vad.is_speech(chunk, RATE)    sys.stdout.write('1' if active else '_')    ring_buffer_flags[ring_buffer_index] = 1 if active else 0    ring_buffer_index += 1    ring_buffer_index %= NUM_WINDOW_CHUNKS    ring_buffer_flags_end[ring_buffer_index_end] = 1 if active else 0    ring_buffer_index_end += 1    ring_buffer_index_end %= NUM_WINDOW_CHUNKS_END    # start point detection    if not triggered:      ring_buffer.append(chunk)      num_voiced = sum(ring_buffer_flags)      if num_voiced > 0.8 NUM_WINDOW_CHUNKS:        sys.stdout.write(' Open ')        triggered = True        start_point = index - CHUNK_SIZE 20 # start point        # voiced_frames.extend(ring_buffer)        ring_buffer.clear()    # end point detection    else:      # voiced_frames.append(chunk)      ring_buffer.append(chunk)      num_unvoiced = NUM_WINDOW_CHUNKS_END - sum(ring_buffer_flags_end)      if num_unvoiced > 0.90 NUM_WINDOW_CHUNKS_END or TimeUse > 10:        sys.stdout.write(' Close ')        triggered = False        got_a_sentence = True    sys.stdout.flush()  sys.stdout.write('/n')  # data = b''.join(voiced_frames)  stream.stop_stream()  print(" done recording")  got_a_sentence = False  # write to file  raw_data.reverse()  for index in range(start_point):    raw_data.pop()  raw_data.reverse()  raw_data = normalize(raw_data)  record_to_file("recording.wav", raw_data, 2)  leave = Truestream.close()