python常见读取语音的3种方法速度对比

# -*- coding: utf-8 -*-
"""
# @Time : 2022/12/29 17:27
# @Author : WangYK
# @Site : 
# @File : check_speed.py.py
# @Software: PyCharm
# @Desc:    本文件实现对比三种常见的都区语音方式的速度区别

"""
import librosa
import soundfile as sf
from scipy.io import wavfile
from time import process_time
from tqdm import tqdm


# 读取方式1
def librosa_loa(filename):
    wav_data,fs=librosa.load(filename,sr=16000)     #float64类型
    #wav_data:[-0.03305054 -0.03561401 -0.03814697]
    return wav_data,fs

#读取方式2
def soundfile_load(filename):
    wav_data,fs=sf.read(filename)                   #float64类型
    #wav_data:[-0.03305054 -0.03561401 -0.03814697]
    return wav_data

#读取方式3
def wavfile_load(filename):
    fs,wav_data=wavfile.read(filename)              #int16类型
    #转为float64类型
    wav_data=wav_data/(32768)
    #wav_data:[-0.03305054 -0.03561401 -0.038114697]
    return wav_data

if __name__ == '__main__':
    filename = ['01.wav']
    filenames = filename * 10000   #重复1万遍,用于对比各个方式耗时
    for filename in tqdm(filenames):
        wav_data=soundfile_load(filename)           # soundfile  读取耗时   1.7031s
        wav_data=librosa_loa(filename)              # librosa    读取耗时   416.23s
        wav_data=wavfile_load(filename)             # wavfile    读取耗时   1.6875s

    print('当前程序耗时：{:.9}s'.fORMat(process_time()))

# 音频的播放，本实验使用pyaudio（代码相对matlab较麻烦，后期简化）
import pyaudio
import wave

chunk = 1024
wf = wave.open(r"C:\Users\zyf\Desktop\Jupyter\1.wav", 'rb')
p = pyaudio.PyAudio()

# 打开声音输出流
stream = p.open(format = p.get_format_from_width(wf.getsampwidth()),
                channels = wf.getnchannels(),
                rate = wf.getframerate(),
                output = True)

# 写声音输出流到声卡进行播放
while True:
    data = wf.readframes(chunk)
    if data == "":
        break
    stream.write(data)

stream.stop_stream()
stream.close()
p.terminate()   # 关闭PyAudio