Merge branch 'Issue71' into 'main'

Issue 71-audio-data-tutorial-sslerror-certificateerror See merge request CMSE/datatools_tutorial_demo!127

Merge branch 'Issue71' into 'main'
Issue 71-audio-data-tutorial-sslerror-certificateerror See merge request CMSE/datatools_tutorial_demo!127
7b3321bc · goodm215 · 05a06064 · 10b5e4d9 · 7b3321bc
Commit 7b3321bc authored 1 year ago by goodm215
--- a/AudioDataTutorial.ipynb
+++ b/AudioDataTutorial.ipynb
@@ -79,7 +79,7 @@
   "source": [
    "import requests\n",
    "\n",
-    "url = 'http://www-mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/Samples/Microsoft/6_Channel_ID.wav'\n",
+    "url = 'http://www.mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/Samples/Microsoft/6_Channel_ID.wav'\n",
    "file='6_Channel_ID.wav'\n",
    "r = requests.get(url, allow_redirects=True)\n",
    "open(file, 'wb').write(r.content)"
@@ -292,7 +292,7 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@@ -306,7 +306,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.6.4"
  }
 },
 "nbformat": 4,

 %% Cell type:markdown id: tags:

 # Audio Tutorial using Scipy

 %% Cell type:markdown id: tags:

 Audio channels can be separated into multiple locatities to give the impression on the viewer of a two or three dimensional space. For instance, most cars have multiple speakers to surround the passengers with sound. This reduces listening fatigue and makes for a more immersive experience. In machine learning, it can be useful to separate audio files into multiple channels so they can be more useful features for locating labels more closely tied to a certain channel.

 %% Cell type:markdown id: tags:

 Adapted from https://publish.illinois.edu/augmentedlistening/tutorials/music-processing/tutorial-1-introduction-to-audio-processing-in-python/

 %% Cell type:code id: tags:

 ``` python
 #!pip install jupyterthemes
 ```

 %% Cell type:code id: tags:

 ``` python
 #!pip install wavio
 ```

 %% Cell type:code id: tags:

 ``` python
 import numpy as np
 import matplotlib.pyplot as plt
 from scipy.io.wavfile import read, write
 from IPython.display import Audio
 from jupyterthemes import jtplot
 import wavio

 jtplot.style()

 %matplotlib inline
 ```

 %% Cell type:markdown id: tags:

 ### Download Multichannel .wav file

 %% Cell type:markdown id: tags:

 Download audio file *6_Channel_ID.wav* from http://www-mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/Samples/Microsoft/6_Channel_ID.wav

 %% Cell type:code id: tags:

 ``` python
 import requests

-url = 'http://www-mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/Samples/Microsoft/6_Channel_ID.wav'
+url = 'http://www.mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/Samples/Microsoft/6_Channel_ID.wav'
 file='6_Channel_ID.wav'
 r = requests.get(url, allow_redirects=True)
 open(file, 'wb').write(r.content)
 ```

 %% Cell type:markdown id: tags:

 ### Read file and split channels

 %% Cell type:markdown id: tags:

 Read .wav file and print frequency

 %% Cell type:code id: tags:

 ``` python
 Fs, data = read('6_Channel_ID.wav')
 print("Sampling Frequency is", Fs)
 ```

 %% Cell type:markdown id: tags:

 Listen to full audio file

 %% Cell type:code id: tags:

 ``` python
 Audio('6_Channel_ID.wav')
 ```

 %% Cell type:markdown id: tags:

 Split audio channels

 %% Cell type:code id: tags:

 ``` python
 FL = data[:,0]
 FR = data[:,1]
 C = data[:,2]
 LF = data[:,3]
 BL = data[:,4]
 BR = data[:,5]
 ```

 %% Cell type:markdown id: tags:

 ### Play audio in Notebook

 %% Cell type:markdown id: tags:

 **Front Left**

 %% Cell type:code id: tags:

 ``` python
 Audio(FL, rate=Fs)
 ```

 %% Cell type:markdown id: tags:

 **Front Right**

 %% Cell type:code id: tags:

 ``` python
 Audio(FR, rate=Fs)
 ```

 %% Cell type:markdown id: tags:

 **Center**

 %% Cell type:code id: tags:

 ``` python
 Audio(C, rate=Fs)
 ```

 %% Cell type:markdown id: tags:

 **Low-frequency effects**

 %% Cell type:code id: tags:

 ``` python
 Audio(LF, rate=Fs)
 ```

 %% Cell type:markdown id: tags:

 **Back Left**

 %% Cell type:code id: tags:

 ``` python
 Audio(BL, rate=Fs)
 ```

 %% Cell type:markdown id: tags:

 **Back Right**

 %% Cell type:code id: tags:

 ``` python
 Audio(BR, rate=Fs)
 ```

 %% Cell type:markdown id: tags:

 ### Plot the Wave form

 %% Cell type:code id: tags:

 ``` python
 plt.figure()
 plt.plot(data)
 plt.xlabel('Sample Index')
 plt.ylabel('Amplitude')
 plt.title('Waveform of Test Audio')
 plt.show()
 ```

 %% Cell type:markdown id: tags:

 ### References

 %% Cell type:markdown id: tags:

 - http://www-mmsp.ece.mcgill.ca/Documents/AudioFormats/WAVE/Samples.html
 - https://publish.illinois.edu/augmentedlistening/tutorials/music-processing/tutorial-1-introduction-to-audio-processing-in-python/