Answers.Body: <p>Fourier transform is used to transform audio data to get more information (features).</p>
  
  <p>For example, raw audio data usually represented by a one-dimensional array, <code>x[n]</code>, which has a length <code>n</code> (number of samples). <code>x[i]</code> is an amplitude value of the i-th sample point.</p>
  
  <p>Using the Fourier transform, your audio data will be represented as a two-dimensional array. Now, <code>x[i]</code> is a not a single value of amplitude, but a list of frequencies which compose original value at the i-th frame (a frame consists of a few samples).</p>
  
  <p>See the image below (from wikipedia), the red graph is an original value of n samples before transformed, and the blue graph is a transformed value of one frame.</p>
  
  <p><a href="https://i.sstatic.net/1OWVu.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/1OWVu.png" alt="enter image description here"></a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-10-03T05:39:22.023Z
Answers.LastActivityDate: 2018-10-03T05:39:22.023Z
Answers.UserDisplayName: malioboro
Body: <p>I've been told this is how I should be preprocessing audio samples, but what information does this method actually give me? What are the alternatives, and why shouldn't I use them?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-10-02T16:11:07.460Z
Comments.Text: OK, I just looked it up. https://ccrma.stanford.edu/~jos/sasp/Mathematical_Definition_STFT.html . . . it seems STFT includes a sliding window function. Probably you would implement STFT using FFT at a lower-level. I was just suspicious that something had been "lost in translation" with "Short-Time" having very similar meaning to "Fast" :-)
Comments.UserDisplayName: Neil Slater
Tags: <data-preprocessing><voice-recognition><fourier-transform>
Title: Why is the short-time Fourier transform used for preprocessing audio samples?
UserDisplayName: 0x777C
ThreadText: # Why is the short-time Fourier transform used for preprocessing audio samples?
  
  (Asked by: username_0 on 2018-10-02)
  
  I've been told this is how I should be preprocessing audio samples, but what information does this method actually give me? What are the alternatives, and why shouldn't I use them?
  
  **Tags:** data-preprocessing, voice-recognition, fourier-transform
  > **Comments:**
  > **username_1**: OK, I just looked it up. https://ccrma.stanford.edu/~jos/sasp/Mathematical_Definition_STFT.html . . . it seems STFT includes a sliding window function. Probably you would implement STFT using FFT at a lower-level. I was just suspicious that something had been "lost in translation" with "Short-Time" having very similar meaning to "Fast" :-)  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2018-10-03. Score: 2 | Accepted answer
  
  Fourier transform is used to transform audio data to get more information (features).
  
  For example, raw audio data usually represented by a one-dimensional array, `x[n]`, which has a length `n` (number of samples). `x[i]` is an amplitude value of the i-th sample point.
  
  Using the Fourier transform, your audio data will be represented as a two-dimensional array. Now, `x[i]` is a not a single value of amplitude, but a list of frequencies which compose original value at the i-th frame (a frame consists of a few samples).
  
  See the image below (from wikipedia), the red graph is an original value of n samples before transformed, and the blue graph is a transformed value of one frame.
  
  [![enter image description here](https://i.sstatic.net/1OWVu.png)](https://i.sstatic.net/1OWVu.png)
  
  
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