ref: 89bc6f4938d3c1e41e351d7cd8314ed3fb3cd433
dir: /python/demos/demo_mfcc.py/
#! /usr/bin/env python import sys from aubio import source, pvoc, mfcc from numpy import vstack, zeros, diff n_filters = 40 # must be 40 for mfcc n_coeffs = 13 if len(sys.argv) < 2: print("Usage: %s <source_filename> [samplerate] [win_s] [hop_s] [mode]" % sys.argv[0]) print(" where [mode] can be 'delta' or 'ddelta' for first and second derivatives") sys.exit(1) source_filename = sys.argv[1] if len(sys.argv) > 2: samplerate = int(sys.argv[2]) else: samplerate = 0 if len(sys.argv) > 3: win_s = int(sys.argv[3]) else: win_s = 512 if len(sys.argv) > 4: hop_s = int(sys.argv[4]) else: hop_s = win_s // 4 if len(sys.argv) > 5: mode = sys.argv[5] else: mode = "default" 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) # compute first and second derivatives if mode in ["delta", "ddelta"]: mfccs = diff(mfccs, axis = 0) if mode == "ddelta": mfccs = diff(mfccs, axis = 0) 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.set_yticks([]) ax.set_ylabel('%d' % i) 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) title = 'MFCC for %s' % source_filename if mode == "delta": title = mode + " " + title elif mode == "ddelta": title = "double-delta" + " " + title wave.set_title(title) plt.show()