感谢cryo的改进版本，我基于下面的测试代码：
#Instead of adding silence at start and end of recording (values=0) I add the original audio . This makes audio sound more natural as volume is >0. See trim()
#I also fixed issue with the previous code - accumulated silence counter needs to be cleared once recording is resumed.
from array import array
from struct import pack
from sys import byteorder
import copy
import pyaudio
import wave
THRESHOLD = 500 # audio levels not normalised.
CHUNK_SIZE = 1024
SILENT_CHUNKS = 3 * 44100 / 1024 # about 3sec
FORMAT = pyaudio.paInt16
FRAME_MAX_VALUE = 2 ** 15 - 1
NORMALIZE_MINUS_ONE_dB = 10 ** (-1.0 / 20)
RATE = 44100
CHANNELS = 1
TRIM_APPEND = RATE / 4
def is_silent(data_chunk):
"""Returns 'True' if below the 'silent' threshold"""
return max(data_chunk) < THRESHOLD
def normalize(data_all):
"""Amplify the volume out to max -1dB"""
# MAXIMUM = 16384
normalize_factor = (float(NORMALIZE_MINUS_ONE_dB * FRAME_MAX_VALUE)
/ max(abs(i) for i in data_all))
r = array('h')
for i in data_all:
r.append(int(i * normalize_factor))
return r
def trim(data_all):
_from = 0
_to = len(data_all) - 1
for i, b in enumerate(data_all):
if abs(b) > THRESHOLD:
_from = max(0, i - TRIM_APPEND)
break
for i, b in enumerate(reversed(data_all)):
if abs(b) > THRESHOLD:
_to = min(len(data_all) - 1, len(data_all) - 1 - i + TRIM_APPEND)
break
return copy.deepcopy(data_all[_from:(_to + 1)])
def record():
"""Record a word or words from the microphone and
return the data as an array of signed shorts."""
p = pyaudio.PyAudio()
stream = p.open(format=FORMAT, channels=CHANNELS, rate=RATE, input=True, output=True, frames_per_buffer=CHUNK_SIZE)
silent_chunks = 0
audio_started = False
data_all = array('h')
while True:
# little endian, signed short
data_chunk = array('h', stream.read(CHUNK_SIZE))
if byteorder == 'big':
data_chunk.byteswap()
data_all.extend(data_chunk)
silent = is_silent(data_chunk)
if audio_started:
if silent:
silent_chunks += 1
if silent_chunks > SILENT_CHUNKS:
break
else:
silent_chunks = 0
elif not silent:
audio_started = True
sample_width = p.get_sample_size(FORMAT)
stream.stop_stream()
stream.close()
p.terminate()
data_all = trim(data_all) # we trim before normalize as threshhold applies to un-normalized wave (as well as is_silent() function)
data_all = normalize(data_all)
return sample_width, data_all
def record_to_file(path):
"Records from the microphone and outputs the resulting data to 'path'"
sample_width, data = record()
data = pack('
wave_file = wave.open(path, 'wb')
wave_file.setnchannels(CHANNELS)
wave_file.setsampwidth(sample_width)
wave_file.setframerate(RATE)
wave_file.writeframes(data)
wave_file.close()
if __name__ == '__main__':
print("Wait in silence to begin recording; wait in silence to terminate")
record_to_file('demo.wav')
print("done - result written to demo.wav")
