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#! /usr/bin/env python
# Implementation of the timescale algorithm according to Dan Ellis, *A Phase
# Vocoder in Matlab*. http://www.ee.columbia.edu/~dpwe/resources/matlab/pvoc/
# This file follows the original implementation, with analysis in a first pass,
# and synthesis in a second pass.
import sys
from aubio import source, sink, pvoc, mfcc, cvec
from aubio import unwrap2pi, float_type
import numpy as np
win_s = 1024
hop_s = win_s / 8 # 87.5 % overlap
warmup = win_s // hop_s - 1
if len(sys.argv) < 3:
print("Usage: %s <source_filename> <output_filename> <rate> [samplerate]".format(sys.argv[0]))
print("""Examples:
# twice faster
{0} track_01.mp3 track_01_faster.wav 2.0
# twice slower
{0} track_02.flac track_02_slower.wav 0.5
# one and a half time faster, resampling first the input to 22050
{0} track_02.flac track_02_slower.wav 1.5 22050""".format(sys.argv[0]))
sys.exit(1)
source_filename = sys.argv[1]
output_filename = sys.argv[2]
rate = float(sys.argv[3])
samplerate = 0 if len(sys.argv) < 5 else int(sys.argv[4])
source_in = source(source_filename, samplerate, hop_s)
samplerate = source_in.samplerate
p = pvoc(win_s, hop_s)
# allocate memory to store norms and phases
n_blocks = source_in.duration // hop_s + 1
# adding an empty frame at end of spectrogram
norms = np.zeros((n_blocks + 1, win_s // 2 + 1), dtype = float_type)
phases = np.zeros((n_blocks + 1, win_s // 2 + 1), dtype = float_type)
block_read = 0
while True:
# read from source
samples, read = source_in()
# compute fftgrain
spec = p(samples)
# store current grain
norms[block_read] = spec.norm
phases[block_read] = spec.phas
# until end of file
if read < hop_s: break
# increment block counter
block_read += 1
# just to make sure
#source_in.close()
sink_out = sink(output_filename, samplerate)
# interpolated time steps (j = alpha * i)
steps = np.arange(0, n_blocks, rate, dtype = float_type)
# initial phase
phas_acc = phases[0]
# excepted phase advance in each bin
phi_advance = np.linspace(0, np.pi * hop_s, win_s / 2 + 1).astype (float_type)
new_grain = cvec(win_s)
for (t, step) in enumerate(steps):
frac = 1. - np.mod(step, 1.0)
# get pair of frames
t_norms = norms[int(step):int(step+2)]
t_phases = phases[int(step):int(step+2)]
# compute interpolated frame
new_grain.norm = frac * t_norms[0] + (1. - frac) * t_norms[1]
new_grain.phas = phas_acc
#print t, step, new_grain.norm
#print t, step, phas_acc
# psola
samples = p.rdo(new_grain)
if t > warmup: # skip the first few frames to warm up phase vocoder
# write to sink
sink_out(samples, hop_s)
# calculate phase advance
dphas = t_phases[1] - t_phases[0] - phi_advance
# unwrap angle to [-pi; pi]
dphas = unwrap2pi(dphas)
# cumulate phase, to be used for next frame
phas_acc += phi_advance + dphas
for t in range(warmup + 1): # purge the last frames from the phase vocoder
new_grain.norm[:] = 0
new_grain.phas[:] = 0
samples = p.rdo(new_grain)
sink_out(samples, read if t == warmup else hop_s)
# just to make sure
#sink_out.close()
format_out = "read {:d} blocks from {:s} at {:d}Hz and rate {:f}, wrote {:d} blocks to {:s}"
print (format_out.format(block_read, source_filename, samplerate, rate,
len(steps), output_filename))
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