为了与@Marco的评论保持一致，您可以查看Scipy库，特别是scipy.io。

from scipy.io import wavfile

要读取您的文件（'filename.wav'），只需执行

output = wavfile.read('filename.wav')

这将输出一个元组（我将其命名为“输出”）：

• output[0]，采样率
• output[1]，要分析的示例数组

这可以通过几行wave（内置）和numpy（显然）来实现。您不需要使用librosa、scipy或soundfile。最新的给我的问题阅读wav文件，这是整个原因，我写在这里现在。

import numpy as np
import wave

# Start opening the file with wave
with wave.open('filename.wav') as f:
    # Read the whole file into a buffer. If you are dealing with a large file
    # then you should read it in blocks and process them separately.
    buffer = f.readframes(f.getnframes())
    # Convert the buffer to a numpy array by checking the size of the sample
    # width in bytes. The output will be a 1D array with interleaved channels.
    interleaved = np.frombuffer(buffer, dtype=f'int{f.getsampwidth()*8}')
    # Reshape it into a 2D array separating the channels in columns.
    data = np.reshape(interleaved, (-1, f.getnchannels()))

我喜欢将它打包到一个函数中，该函数返回采样频率并与pathlib.Path对象一起工作。这样就可以使用sounddevice播放

# play_wav.py
import sounddevice as sd
import numpy as np
import wave

from typing import Tuple
from pathlib import Path

# Utility function that reads the whole `wav` file content into a numpy array
def wave_read(filename: Path) -> Tuple[np.ndarray, int]:
    with wave.open(str(filename), 'rb') as f:
        buffer = f.readframes(f.getnframes())
        inter = np.frombuffer(buffer, dtype=f'int{f.getsampwidth()*8}')
        return np.reshape(inter, (-1, f.getnchannels())), f.getframerate()

if __name__ == '__main__':
    # Play all files in the current directory
    for wav_file in Path().glob('*.wav'):
        print(f"Playing {wav_file}")
        data, fs = wave_read(wav_file)
        sd.play(data, samplerate=fs, blocking=True)