import unittest
import os
import numpy as np
from scipy.io import wavfile
from scipy.fftpack import fft
from sprocket.speech import Shifter
dirpath = os.path.dirname(os.path.realpath(__file__))
saveflag = False
class ShifterTest(unittest.TestCase):
def test_shifter(self):
path = dirpath + '/data/test16000.wav'
fs, x = wavfile.read(path)
for f0rate in (0.5, 0.75, 1.0, 1.5, 2.0):
if f0rate < 1:
completion = True
else:
completion = False
shifter = Shifter(fs, f0rate=f0rate, shiftms=10)
transformed_x = shifter.f0transform(x, completion=completion)
assert len(x) == len(transformed_x)
if saveflag:
fpath = path + str(f0rate) + '.wav'
wavfile.write(fpath, fs, transformed_x.astype(np.int16))
def test_high_frequency_completion(self):
path = dirpath + '/data/test16000.wav'
fs, x = wavfile.read(path)
f0rate = 0.5
shifter = Shifter(fs, f0rate=f0rate)
mod_x = shifter.f0transform(x, completion=False)
mod_xc = shifter.f0transform(x, completion=True)
assert len(mod_x) == len(mod_xc)
N = 512
fl = int(fs * 25 / 1000)
win = np.hanning(fl)
sts = [1000, 5000, 10000, 20000]
for st in sts:
# confirm w/o completion
f_mod_x = fft(mod_x[st: st + fl] / 2**16 * win)
amp_mod_x = 20.0 * np.log10(np.abs(f_mod_x))
# confirm w/ completion
f_mod_xc = fft(mod_xc[st: st + fl] / 2**16 * win)
amp_mod_xc = 20.0 * np.log10(np.abs(f_mod_xc))
assert np.mean(amp_mod_x[N // 4:] < np.mean(amp_mod_xc[N // 4:]))
