I want to convert mp3 files using courier's transform and export as spectrogram.Then I need to save as PNG file containing all frequencies of my mp3. How can I do that by using jupyter notebook?
Most of the following comes from: http://myinspirationinformation.com/uncategorized/audio-signals-in-python/
The mp3 sample comes from the BBC bird song site.
I ran this in Jupyter notebook using Python 3.6 running under Linux Mint.
from IPython.display import Audio, display
import matplotlib.pyplot as plt
from numpy import fft
import numpy as np
import pydub
from scipy.fftpack import fft
from scipy.io import wavfile
import scipy
import urllib
AUDIO_URL='http://downloads.bbc.co.uk/rmhttp/radio4/science/Birdsong-Blackbird.mp3'
temp_folder = '/home/bill/data/tmp/'
urllib.request.urlretrieve(AUDIO_URL, temp_folder+'file.mp3')
#read mp3 file
mp3 = pydub.AudioSegment.from_mp3(temp_folder+"file.mp3")
#convert to wav
mp3.export(temp_folder+"file.wav", format="wav")
#read wav file
freq, audio_data = scipy.io.wavfile.read(temp_folder+"file.wav")
length = audio_data.shape[0]/freq
channels = audio_data.shape[1]
print('freq: {} length: {} channels: {}'.format(freq, length, channels))
#if stereo grab both channels
channel1 = audio_data[:,0] #left
channel2 = audio_data[:,1] #right
#create a time variable in seconds
time = np.arange(0, float(audio_data.shape[0]), 1) / freq
#plot amplitude (or loudness) over time
plt.figure(1)
plt.subplot(211)
plt.plot(time, channel1, linewidth=0.01, alpha=0.7, color='#ff7f00')
plt.xlabel('Time (s)')
plt.ylabel('Amplitude')
plt.subplot(212)
plt.plot(time, channel2, linewidth=0.01, alpha=0.7, color='#ff7f00')
plt.xlabel('Time (s)')
plt.ylabel('Amplitude')
plt.show()
fourier=fft(channel1)
n = len(channel1)
fourier = fourier[0:int(n/2)]
# scale by the number of points so that the magnitude does not depend on the length
fourier = fourier / float(n)
#calculate the frequency at each point in Hz
freq_array = np.arange(0, (n/2), 1.0) * (freq*1.0/n);
plt.plot(freq_array/1000, 10*np.log10(fourier), color='#ff7f00', linewidth=0.02)
plt.xlabel('frequency in kHz')
plt.ylabel('power in dB')
plt.savefig(temp_folder+'spectrogram.png')