音频处理发现的比较简单的代码，原作者代码在github：GitHub - silencesmile/python_wav: 对音频文件的处理：音频信息，读取内容，获取时长，切割音频，pcm与wav互转

 

可以按给定的开始和结束时间调用代码批处理，示例：

这是原音频文件的信息存储在csv文件，目标是按照给定的开始结束时间切割成多个小的音频片段

bg列为开始时间单位为秒，ed列为结束时间单位为秒，wav列为想要的音频片段命名

 批处理代码，调用了get_second_part_wav函数：

from pydub import AudioSegment
def get_second_part_wav(main_wav_path, start_time, end_time,part_wav_path):
    # 原音频文件路径,开始时间,结束时间,切分音频的存储路径
    start_time = int(start_time) * 1000
    end_time = int(end_time)  * 1000
    sound = AudioSegment.from_file(main_wav_path)
    word = sound[start_time:end_time]
    word.export(part_wav_path, format="wav")


audio_teacher = pd.read_csv('try1.csv', encoding='utf-8')
start_list = audio_teacher['bg'].tolist()
end_list = audio_teacher['ed'].tolist()
wav_list = audio_teacher['wav'].tolist()

for i in range(len(start_list)):
    start_time = start_list[i]
    end_time = end_list[i]
    get_second_part_wav('audio/try1.mp4', start_time, end_time, 'audio_sep/' + str(wav_list[i]))

原作者的可以根据需要调用的代码 ：

# -*- coding:utf8 -*-
'''
auth： Young
公众号：Python疯子 （Hold2Crazy）
'''
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_file(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_file(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_file(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()