<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>

CC BY-SA 4.0
2018-10-03T05:39:22.023Z
2018-10-03T05:39:22.023Z
malioboro
<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>

CC BY-SA 4.0
2018-10-02T16:11:07.460Z
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" :-)
Neil Slater
<data-preprocessing><voice-recognition><fourier-transform>
Why is the short-time Fourier transform used for preprocessing audio samples?
0x777C
# 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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