def transform_f0_from_list(speaker, f0rate, wav_fs, list_file, wav_dir):
"""Transform f0 from list
Transform F0 of the waveforms based on `f0rate` and
save into `wav_dir` with `speaker`_`$f0rate` label
Parameters
---------
speaker : str,
Label of the source speaker
f0rate : float,
File path of the list file of the speaker
wav_fs : int,
Sampling frequency of the waveform
listfile : str, path-like,
File path of the list file of the speaker
wav_dir : str, path-like,
Directory path of the waveform
"""
# open list file
with open(list_file, 'r') as fp:
files = fp.readlines()
# Construct Shifter class
shifter = Shifter(wav_fs, f0rate=f0rate)
# check output directory
transformed_wavdir = os.path.join(wav_dir, speaker + '_' + str(f0rate))
if not os.path.exists(transformed_wavdir):
os.makedirs(transformed_wavdir)
for f in files:
# open wave file
f = f.rstrip()
wavf = os.path.join(wav_dir, f + '.wav')
# output file path
transformed_wavpath = os.path.join(transformed_wavdir,
os.path.basename(wavf))
# flag for completion of high frequency range
if f0rate < 1.0:
completion = True
else:
completion = False
if not os.path.exists(transformed_wavpath):
# transform F0 of waveform
fs, x = wavfile.read(wavf)
x = np.array(x, dtype=np.float)
x = low_cut_filter(x, fs, cutoff=70)
assert fs == wav_fs
transformed_x = shifter.f0transform(x, completion=completion)
wavfile.write(transformed_wavpath, fs,
transformed_x.astype(np.int16))
print('F0 transformed wav file: ' + transformed_wavpath)
else:
print('F0 transformed wav file already exists: ' +
transformed_wavpath)
def transform_f0_from_list(speaker, f0rate, wav_fs, list_file, wav_dir):
"""Transform f0 from list
Transform F0 of the waveforms based on `f0rate` and
save into `wav_dir` with `speaker`_`$f0rate` label
Parameters
---------
speaker : str,
Label of the source speaker
f0rate : float,
File path of the list file of the speaker
wav_fs : int,
Sampling frequency of the waveform
listfile : str, path-like,
File path of the list file of the speaker
wav_dir : str, path-like,
Directory path of the waveform
"""
# open list file
with open(list_file, 'r') as fp:
files = fp.readlines()
# Construct Shifter class
shifter = Shifter(wav_fs, f0rate=f0rate)
# check output directory
transformed_wavdir = os.path.join(wav_dir, speaker + '_' + str(f0rate))
if not os.path.exists(transformed_wavdir):
os.makedirs(transformed_wavdir)
for f in files:
# open wave file
f = f.rstrip()
wavf = os.path.join(wav_dir, f + '.wav')
# output file path
transformed_wavpath = os.path.join(
transformed_wavdir, os.path.basename(wavf))
# flag for completion of high frequency range
if f0rate < 1.0:
completion = True
else:
completion = False
if not os.path.exists(transformed_wavpath):
# transform F0 of waveform
fs, x = wavfile.read(wavf)
x = np.array(x, dtype=np.float)
x = low_cut_filter(x, fs, cutoff=70)
assert fs == wav_fs
transformed_x = shifter.f0transform(x, completion=completion)
wavfile.write(transformed_wavpath, fs,
transformed_x.astype(np.int16))
print('F0 transformed wav file: ' + transformed_wavpath)
else:
print('F0 transformed wav file already exists: ' + transformed_wavpath)
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)
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_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 transform_f0_from_list(speaker, f0rate, wav_fs, list_file, wav_dir):
# open list file
with open(list_file, 'r') as fp:
files = fp.readlines()
# Construct Shifter class
shifter = Shifter(wav_fs, f0rate=f0rate)
# check output directory
transformed_wavdir = os.path.join(wav_dir, speaker + '_' + str(f0rate))
if not os.path.exists(transformed_wavdir):
os.makedirs(transformed_wavdir)
for f in files:
# open wave file
f = f.rstrip()
wavf = os.path.join(wav_dir, f + '.wav')
# output file path
transformed_wavpath = os.path.join(transformed_wavdir,
os.path.basename(wavf))
# flag for completion of high frequency range
if f0rate < 1.0:
completion = True
else:
completion = False
if not os.path.exists(transformed_wavpath):
# transform F0 of waveform
fs, x = wavfile.read(wavf)
x = np.array(x, dtype=np.float)
assert fs == wav_fs
transformed_x = shifter.f0transform(x, completion=completion)
wavfile.write(transformed_wavpath, fs,
transformed_x.astype(np.int16))
print('F0 transformed wav file: ' + transformed_wavpath)
else:
print('F0 transformed wav file already exists: ' +
transformed_wavpath)
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:]))
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:]))