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@dalsh
Created November 15, 2017 12:32
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Spectrograms with Scipy and Matplotlib
import matplotlib.colors as colors
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from scipy.io import wavfile
BASEDIR = './'
OUTDIR = BASEDIR + 'spectrograms/'
def save_spectrogram(voice_name):
sample_rate, samples = wavfile.read(BASEDIR + 'samples/' + voice_name + '.wav')
# average all channels
avg = np.add(samples[:,0],samples[:,0])/2
# generate spectrogram
f, t, Sxx = signal.spectrogram(avg, sample_rate)
# make a figure without borders or padding
fig=plt.figure(frameon=False)
fig.set_size_inches(512/32,512/32) # 512 pixels, 32 dpi
mesh = fig.add_subplot(1,1,1)
mesh.pcolormesh(t, f, Sxx,
norm=colors.SymLogNorm(linthresh=0.00001), # magic value threshold set so it looks good
cmap='Greys')
plt.axis('off')
mesh.axes.get_xaxis().set_visible(False)
mesh.axes.get_yaxis().set_visible(False)
fig.subplots_adjust(bottom = 0)
fig.subplots_adjust(top = 1)
fig.subplots_adjust(right = 1)
fig.subplots_adjust(left = 0)
fig.savefig(OUTDIR + voice_name + '.png', transparent=True, dpi = 32)
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