Fix calculation of SNR value in tutorial (pytorch#2285)

Summary:
The calculation of the SNR in tha data augmentation examples seems to be wrong to me:

![image](https://user-images.githubusercontent.com/173624/159487032-c60470c6-ef8e-48a0-ad5e-a117fcb8d606.png)

If we start from the definition of the signal-to-noise ratio using the root mean square value we get:

```
SNR = 20 log10 ( rms(scale * speech) / rms(noise) )
```
this can be transformed to
```
scale = 10^(SNR/20) rms(noise) / rms(speech)
```
In the example not `rms` is used but `lambda x: x.norm(p=2)`, but as we have the same length of the speech and noise signal, we have
```
rms(noise) / rms(speech) = noise.norm(p=2) / speech.norm(p=2)
```
this would lead us to:
```
10^(SNR/20) = e^(SNR / 10)
```
which is not true.

Hence I changed `e^(SNR / 10)` to `10^(SNR/20)`.

For the proposed SNR values of 20 dB, 10 dB, 3 dB the value of the scale would change from 7.39, 2.72, 1.35 to 10.0, 3.16, 1.41.

Pull Request resolved: pytorch#2285

Reviewed By: nateanl

Differential Revision: D35047737

Pulled By: mthrok

fbshipit-source-id: ac24c8fd48ef06b4b611e35163084644330a3ef3

examples/tutorials/audio_data_augmentation_tutorial.py

@@ -350,7 +350,7 @@ def get_noise_sample(*, resample=None):
 snr_dbs = [20, 10, 3]
 noisy_speeches = []
 for snr_db in snr_dbs:
-    snr = math.exp(snr_db / 10)
+    snr = 10 ** (snr_db / 20)
     scale = snr * noise_power / speech_power
     noisy_speeches.append((scale * speech + noise) / 2)