ifft(fft(audio))只是噪音 [英] ifft(fft(audio)) is just noise

问题描述

是将它们嵌套(iff(fft(audio)))还是尝试逐窗口显示(window音频，执行fft，执行ifft，然后反转窗口，用eps替换零，然后合并回样本(在管道中的此处和此处尝试abs))，我只会得到噪音.

whether i just nest them (iff(fft(audio))) or try window-by-window (window the audio, do the fft, do the ifft, then invert the window, replacing zero with eps, then merge the samples back (trying abs here and there in the pipelines)) i get only noise.

我知道ifft仅与fft逆，具有无限精度算术，无限多个样本等(对吗?)，我正在使用64位浮点和44kHZ采样率.但是，我希望至少能够听到原始音频.

i know the ifft is only inverse to the fft with infinite precision arithmetic, infinitely many samples, etc (right?) i'm working with 64bit floating point and 44kHZ sample rate. but, i would expect to be able to at least hear the original audio.

我的错误是实用的还是理论的?如果有错误，我可以给出代码.

is my error practical or theoretical? i can give code, if it's a bug.

推荐答案

基于JoeKington的评论，我下载了

Building on JoeKington's comment, I have downloaded this file, and tried the following

>>> import scipy.io.wavfile
>>> rate, data = scipy.io.wavfile.read('wahoo.wav')
>>> data
array([134, 134, 134, ..., 124, 124, 124], dtype=uint8)
>>> data_bis = np.fft.ifft(np.fft.fft(data))
>>> data_bis
array([ 134. +6.68519934e-14j,  134. -4.57982480e-14j,
        134. -1.78967708e-14j, ...,  124. -2.09835513e-14j,
        124. -1.61750469e-14j,  124. -2.14867343e-14j])
>>> data_bis = data_bis.astype('uint8')
C:\Users\Jaime y Eva\Desktop\stack_exchange.py:1: ComplexWarning: Casting complex values to real discards the imaginary part
  # -*- coding: utf-8 -*-
>>> data_bis
array([134, 133, 133, ..., 123, 123, 123], dtype=uint8)
>>> scipy.io.wavfile.write('wahoo_bis.wav', rate, data_bis)

结果文件的播放与原始文件完全相同.

And the resulting file plays exactly the same as the original one.

因此将返回的复数值转换为实数仅是问题的一半(并且您可能想使用np.abs而不是data.real，就像上面的代码隐式地一样)，然后还需要重铸浮点数点号到适当的位深度的uint.

So turning the return complex values into reals is only half the problem (and you may want to go with np.abs rather than data.real, as the code above implicitly does), and you then also need to recast your floating point numbers to uints of the apropriate bit-depth.

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