filepath = "data/" # 添加路径 filename = os.listdir(filepath) # 得到文件夹下的所有文件名称 #f = wave.open(filepath + filename[1], 'rb') #print(filename) for i in range(len(filename)): with open("data/"+failename[i], 'rb') as pcmfile: pcmdata = pcmfile.read() with wave.open("data/"+filename[i][:-3] + '.wav', 'wb') as wavfile: wavfile.setparams((1, 2, 16000, 0, 'NONE', 'NONE')) wavfile.writeframes(pcmdata)

• 利用语音停顿切分

利用 split_on_silence（sound，min_silence_len,   silence_thresh,    keep_silence=400）函数

第一个参数为待分割音频，第二个为多少秒“没声”代表沉默，第三个为分贝小于多少dBFS时代表沉默，第四个为为截出的每个音频添加多少ms无声

from pydub import AudioSegment
from pydub.silence import split_on_silence
sound = AudioSegment.from_mp3("movie300.wav")
loudness = sound.dBFS
#print(loudness)
chunks = split_on_silence(sound,
    # must be silent for at least half a second,沉默半秒
    min_silence_len=430,
    # consider it silent if quieter than -16 dBFS
    silence_thresh=-45,
    keep_silence=400
print('总分段：', len(chunks))
# 放弃长度小于2秒的录音片段
for i in list(range(len(chunks)))[::-1]:
    if len(chunks[i]) <= 2000 or len(chunks[i]) >= 10000:
        chunks.pop(i)
print('取有效分段(大于2s小于10s)：', len(chunks))
for x in range(0,int(len(sound)/1000)):
    print(x,sound[x*1000:(x+1)*1000].max_dBFS)
for i, chunk in enumerate(chunks):
    chunk.export("cutFilter300/chunk{0}.wav".format(i), format="wav")
    #print(i)

将pcm文件批量处理成wav文件import waveimport osfilepath = "data/" # 添加路径filename = os.listdir(filepath) # 得到文件夹下的所有文件名称#f = wave.open(filepath + filename[1], 'rb')#print(filename)for i in range(len(fi...