ref: bbc62b58100bcb0cb0055abea9dcd46803b6d8f4
dir: /python/demos/demo_mfcc.py/
#! /usr/bin/env python
import sys
from aubio import source, pvoc, mfcc
from numpy import array, vstack, zeros
win_s = 512 # fft size
hop_s = win_s / 4 # hop size
n_filters = 40 # must be 40 for mfcc
n_coeffs = 13
samplerate = 44100
if len(sys.argv) < 2:
print "Usage: %s <source_filename>" % sys.argv[0]
sys.exit(1)
source_filename = sys.argv[1]
samplerate = 0
if len( sys.argv ) > 2: samplerate = int(sys.argv[2])
s = source(source_filename, samplerate, hop_s)
samplerate = s.samplerate
p = pvoc(win_s, hop_s)
m = mfcc(win_s, n_filters, n_coeffs, samplerate)
mfccs = zeros([n_coeffs,])
frames_read = 0
while True:
samples, read = s()
spec = p(samples)
mfcc_out = m(spec)
mfccs = vstack((mfccs, mfcc_out))
frames_read += read
if read < hop_s: break
# do plotting
from numpy import arange
from demo_waveform_plot import get_waveform_plot
from demo_waveform_plot import set_xlabels_sample2time
import matplotlib.pyplot as plt
fig = plt.figure()
plt.rc('lines',linewidth='.8')
wave = plt.axes([0.1, 0.75, 0.8, 0.19])
get_waveform_plot( source_filename, samplerate, block_size = hop_s, ax = wave)
wave.xaxis.set_visible(False)
wave.yaxis.set_visible(False)
all_times = arange(mfccs.shape[0]) * hop_s
n_coeffs = mfccs.shape[1]
for i in range(n_coeffs):
ax = plt.axes ( [0.1, 0.75 - ((i+1) * 0.65 / n_coeffs), 0.8, 0.65 / n_coeffs], sharex = wave )
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
ax.plot(all_times, mfccs.T[i])
# add time to the last axis
set_xlabels_sample2time( ax, frames_read, samplerate)
#plt.ylabel('spectral descriptor value')
ax.xaxis.set_visible(True)
wave.set_title('MFCC for %s' % source_filename)
plt.show()