python 中的降噪算法不起作用

我一直在尝试使用noisereduce pypi 算法来减少音频文件的噪音，但它给了我一个错误：

Traceback (most recent call last):
  File "C:/Users/Seif Koretum/Desktop/noise_reduce/main.py", line 22, in <module>
    reduced_noise = nr.reduce_noise(y=data, sr=rate)
  File "C:\Users\Seif Koretum\Desktop\noise_reduce\venv\lib\site-packages\noisereduce\noisereduce.py", line 594, in reduce_noise
    return sg.get_traces()
  File "C:\Users\Seif Koretum\Desktop\noise_reduce\venv\lib\site-packages\noisereduce\noisereduce.py", line 232, in get_traces
    filtered_chunk = self.filter_chunk(start_frame=0, end_frame=end_frame)
  File "C:\Users\Seif Koretum\Desktop\noise_reduce\venv\lib\site-packages\noisereduce\noisereduce.py", line 162, in filter_chunk
    padded_chunk = self._read_chunk(i1, i2)
  File "C:\Users\Seif Koretum\Desktop\noise_reduce\venv\lib\site-packages\noisereduce\noisereduce.py", line 154, in _read_chunk
    chunk = np.zeros((self.n_channels, i2 - i1))
numpy.core._exceptions.MemoryError: Unable to allocate 98.6 GiB for an array with shape (220500, 60002) and data type float64

我的代码基于录制音频文件，然后消除噪音，然后播放此音频：

from scipy.io import wavfile as wav
from scipy.io.wavfile import write
import sounddevice as sd
from playsound import playsound
import noisereduce as nr


fs = 44100  # Sample rate
seconds = 5   # Duration of recording

myrecording = sd.rec(int(seconds * fs), samplerate=fs, channels=2)
sd.wait()  # Wait until recording is finished
write('sample2.wav', fs, myrecording)

#SEARCH FOR NOISEREDUCE PYPI
# # load data
rate, data = wav.read("sample2.wav")
# perform noise reduction
reduced_noise = nr.reduce_noise(y=data, sr=rate)


filename = 'sample2.wav'
playsound(filename)

您必须使用评论中建议的重塑，然后在保存之前重塑回来：

from scipy.io import wavfile
import noisereduce as nr
import numpy as np

# load data
rate, data = wavfile.read("Why Rust (online-audio-converter.com) (1).wav")
orig_shape = data.shape
data = np.reshape(data, (2, -1))

# perform noise reduction
# optimized for speech
reduced_noise = nr.reduce_noise(
    y=data,
    sr=rate,
    stationary=True
)

wavfile.write("mywav_reduced_noise.wav", rate, reduced_noise.reshape(orig_shape))