基于python3下wav文件的批量分割
发布日期：2022/8/24 13:43:24 浏览量：
基于python3下wav文件的批量分割
import os
import wave
import contextlib
import numpy as np
import matplotlib.pyplot as plt
from scipy.io import wavfile
from pydub import AudioSegment
def wav_infos(wav_path):
’’’
获取音频信息
:param wav_path: 音频路径
:return: [1, 2, 8000, 51158, ’NONE’, ’not compressed’]
对应关系：声道，采样宽度，帧速率，帧数，唯一标识，无损
’’’
with wave.open(wav_path, "rb") as f:
f = wave.open(wav_path)
return list(f.getparams())
def read_wav(wav_path):
’’’
读取音频文件内容:只能读取单声道的音频文件, 这个比较耗时
:param wav_path: 音频路径
:return: 音频内容
’’’
with wave.open(wav_path, "rb") as f:
# 读取格式信息
# 一次性返回所有的WAV文件的格式信息，它返回的是一个组元(tuple)：声道数, 量化位数（byte单位）, 采
# 样频率, 采样点数, 压缩类型, 压缩类型的描述。wave模块只支持非压缩的数据，因此可以忽略最后两个信息
params = f.getparams()
nchannels, sampwidth, framerate, nframes = params[:4]
# 读取声音数据，传递一个参数指定需要读取的长度（以取样点为单位）
str_data = f.readframes(nframes)
return str_data
def get_wav_time(wav_path):
’’’
获取音频文件是时长
:param wav_path: 音频路径
:return: 音频时长 (单位秒)
’’’
with contextlib.closing(wave.open(wav_path, ’r’)) as f:
frames = f.getnframes()
rate = f.getframerate()
duration = frames / float(rate)
return duration
def get_ms_part_wav(main_wav_path, start_time, end_time, part_wav_path):
’’’
音频切片，获取部分音频 单位是毫秒级别
:param main_wav_path: 原音频文件路径
:param start_time: 截取的开始时间
:param end_time: 截取的结束时间
:param part_wav_path: 截取后的音频路径
:return:
’’’
start_time = int(start_time)
end_time = int(end_time)
sound = AudioSegment.from_mp3(main_wav_path)
word = sound[start_time:end_time]
word.export(part_wav_path, format="wav")
def get_second_part_wav(main_wav_path, start_time, end_time, part_wav_path):
’’’
音频切片，获取部分音频 单位是秒级别
:param main_wav_path: 原音频文件路径
:param start_time: 截取的开始时间
:param end_time: 截取的结束时间
:param part_wav_path: 截取后的音频路径
:return:
’’’
start_time = int(start_time) * 1000
end_time = int(end_time) * 1000
sound = AudioSegment.from_mp3(main_wav_path)
word = sound[start_time:end_time]
word.export(part_wav_path, format="wav")
def get_minute_part_wav(main_wav_path, start_time, end_time, part_wav_path):
’’’
音频切片，获取部分音频 分钟:秒数 时间样式："12:35"
:param main_wav_path: 原音频文件路径
:param start_time: 截取的开始时间
:param end_time: 截取的结束时间
:param part_wav_path: 截取后的音频路径
:return:
’’’
start_time = (int(start_time.split(’:’)[0])*60+int(start_time.split(’:’)[1]))*1000
end_time = (int(end_time.split(’:’)[0])*60+int(end_time.split(’:’)[1]))*1000
sound = AudioSegment.from_mp3(main_wav_path)
word = sound[start_time:end_time]
word.export(part_wav_path, format="wav")
def wav_to_pcm(wav_path, pcm_path):
’’’
wav文件转为pcm文件
:param wav_path:wav文件路径
:param pcm_path:要存储的pcm文件路径
:return: 返回结果
’’’
f = open(wav_path, "rb")
f.seek(0)
f.read(44)
data = np.fromfile(f, dtype=np.int16)
data.tofile(pcm_path)
def pcm_to_wav(pcm_path, wav_path):
’’’
pcm文件转为wav文件
:param pcm_path: pcm文件路径
:param wav_path: wav文件路径
:return:
’’’
f = open(pcm_path,’rb’)
str_data = f.read()
wave_out=wave.open(wav_path,’wb’)
wave_out.setnchannels(1)
wave_out.setsampwidth(2)
wave_out.setframerate(8000)
wave_out.writeframes(str_data)
# 音频对应的波形图
def wav_waveform(wave_path):
’’’
音频对应的波形图
:param wave_path: 音频路径
:return:
’’’
file = wave.open(wave_path)
# print(’---------声音信息------------’)
# for item in enumerate(WAVE.getparams()):
# print(item)
a = file.getparams().nframes # 帧总数
f = file.getparams().framerate # 采样频率
sample_time = 1 / f # 采样点的时间间隔
time = a / f # 声音信号的长度
sample_frequency, audio_sequence = wavfile.read(wave_path)
# print(audio_sequence) # 声音信号每一帧的“大小”
x_seq = np.arange(0, time, sample_time)
plt.plot(x_seq, audio_sequence, ’blue’)
plt.xlabel("time (s)")
plt.show()
if __name__ == ’__main__’:
path = r’C:/123/’ # 原音频目录
path_segment = r’C:/234/’ # 切割后的音频目录
print(’开始切割音频！’)
time_segment = 100 # 切割后短音频的时长
for root, dir, files in os.walk(path):
for i in range(len(files)):
audio = root + files[i]
time_all = int(get_wav_time(audio) * 1000) # 转换成毫秒
start_time = 0 # 从第0ms开始切割
index = 1 # 切割后的序号名，从序号1开始命令
while start_time <= time_all - time_segment:
# print(str(i)+ ’: ’ + str(index))
end_time = start_time + time_segment
aduio_segment = path_segment + files[i][:-4] + ’_’ + str(index) + ’.wav’
get_ms_part_wav(audio, start_time, end_time, aduio_segment)
start_time += time_segment
index += 1
# 接下来这两行是为了将最终能够不足time_segment时长的音频剪下来
aduio_segment = path_segment + files[i][:-4] + ’_’ + str(index) + ’.wav’
get_ms_part_wav(audio, start_time, time_all, aduio_segment)
print(’音频切割完成！’)
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