def test_voice_conversion_fullset(tmpdir):
result_root = pathlib.Path(tmpdir)
sys.argv = \
[
sys.argv[0],
'--source',
str(dataset.get_dataset_path(dataset.CLB_DIR, fullset=True)),
'--target',
str(dataset.get_dataset_path(dataset.SLT_DIR, fullset=True)),
'--result-dir', str(result_root),
'--converter-seed', '0',
'--max-files', '100',
'--skip-files', '3',
str(dataset.get_wav_path(dataset.CLB_DIR/'arctic_a0001.wav',
fullset=True)),
str(dataset.get_wav_path(dataset.CLB_DIR/'arctic_a0002.wav',
fullset=True)),
str(dataset.get_wav_path(dataset.CLB_DIR/'arctic_a0003.wav',
fullset=True)),
]
np.random.seed(0)
cv.main()
results = ['arctic_a0001', 'arctic_a0002', 'arctic_a0003']
for result in results:
result_path = (result_root / result).with_suffix('.diff.wav')
assert result_path.is_file()
expected = make_expected_feature(result + '.wav', fullset=True)
actual = kwiiyatta.analyze_wav(result_path)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, actual)
assert_any.between(0.068, f0_diff, 0.12)
assert_any.between(0.49, spec_diff, 0.59)
assert_any.between(0.050, ape_diff, 0.074)
assert_any.between(0.10, mcep_diff, 0.11)
for result in results:
result_path = (result_root / result).with_suffix('.synth.wav')
assert result_path.is_file()
expected = make_expected_feature(result + '.wav', fullset=True)
actual = kwiiyatta.analyze_wav(result_path)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, actual)
assert_any.between(0.062, f0_diff, 0.075)
assert_any.between(0.48, spec_diff, 0.56)
assert_any.between(0.10, ape_diff, 0.13)
assert_any.between(0.10, mcep_diff, 0.11)
def test_resample_down(fs1, fs2, wavfile, frame_period):
if fs2 < fs1:
fs1, fs2 = fs2, fs1
a1 = feature.get_analyzer(dataset.get_wav_path(wavfile, fs=fs1),
frame_period=frame_period)
a2 = feature.get_analyzer(dataset.get_wav_path(wavfile, fs=fs2),
frame_period=frame_period)
a2_r = kwiiyatta.resample(a2, fs1)
a2._spectrum_envelope = None
a2._aperiodicity = None
a2._mel_cepstrum.data = None
assert a1.fs == a2_r.fs
assert (feature.calc_diff(a2_r.mel_cepstrum.data,
a2.resample_mel_cepstrum(a2_r.fs).data) == 0)
assert feature.calc_diff(a2_r.f0, a2.f0) == 0
assert (feature.calc_powered_diff(a2_r.spectrum_envelope,
a2.resample_spectrum_envelope(
a2_r.fs)) == 0)
assert (feature.calc_diff(a2_r.aperiodicity,
a2.resample_aperiodicity(a2_r.fs)) == 0)
assert a2.mel_cepstrum.order == a2_r.mel_cepstrum.order
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(a1, a2_r)
assert_any.between(0.0012, f0_diff, 0.014)
assert_any.between(0.0025, spec_diff, 0.0094)
assert_any.between(0.0015, ape_diff, 0.048)
assert_any.between(0.011, mcep_diff, 0.031)
a2_r_wav = a2_r.synthesize()
a2_r_s = kwiiyatta.Analyzer(a2_r_wav, frame_period=frame_period)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(a1, a2_r_s)
assert_any.between(0.055, f0_diff, 0.11)
assert_any.between(0.20, spec_diff, 0.23)
assert_any.between(0.072, ape_diff, 0.10)
assert_any.between(0.038, mcep_diff, 0.056)
f2 = kwiiyatta.feature(a2)
f2.extract_mel_cepstrum()
f2.spectrum_envelope = None
f2_mcep_r = f2.resample_mel_cepstrum(a1.fs)
mcep_diff = feature.calc_diff(a1.mel_cepstrum.data, f2_mcep_r.data)
assert_any.between(0.014, mcep_diff, 0.041)
a2_mcep_r = kwiiyatta.resample(a2.mel_cepstrum, a1.fs)
mcep_diff = feature.calc_diff(a2_mcep_r.data, f2_mcep_r.data)
assert mcep_diff == 0
def test_mlsa_filter(fs1, fs2):
np.random.seed(0)
clb = feature.get_analyzer(dataset.get_wav_path(dataset.CLB_WAV, fs=fs1))
slt = feature.get_analyzer(dataset.get_wav_path(dataset.SLT_WAV, fs=fs2))
slt_aligned = kwiiyatta.align(slt, clb)
mcep_diff = copy.copy(slt_aligned.mel_cepstrum)
mcep_diff.data = mcep_diff.data - clb.mel_cepstrum.resample_data(slt.fs)
result = kwiiyatta.apply_mlsa_filter(clb.wavdata, mcep_diff)
expected = kwiiyatta.feature(clb)
if clb.fs > slt.fs:
slt_shape = clb.spectrum_len * slt.fs // clb.fs
expected.spectrum_envelope = \
np.hstack((
feature.override_power(
slt_aligned.reshaped_spectrum_envelope(slt_shape),
clb.spectrum_envelope[:, :slt_shape]
),
clb.spectrum_envelope[:, slt_shape:]
))
else:
expected.spectrum_envelope = \
slt_aligned.resample_spectrum_envelope(clb.fs)
feature.override_spectrum_power(expected, clb)
actual = kwiiyatta.Analyzer(result)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, actual)
assert_any.between(0.051, f0_diff, 0.078)
assert_any.between(0.32, spec_diff, 0.55)
assert_any.between(0.039, ape_diff, 0.073)
assert_any.between(0.038, mcep_diff, 0.088)
def test_voice_resynthesis_diffvc(check, tmpdir):
result_root = pathlib.Path(tmpdir)
sys.argv = [
sys.argv[0],
str(dataset.CLB_WAV), "--result-dir",
str(result_root), "--mcep", "--mcep-order", "48", "--carrier",
str(dataset.SLT_WAV), "--diffvc"
]
rv.main()
result_file = result_root / 'arctic_a0001.wav'
assert result_file.is_file()
clb = feature.get_analyzer(dataset.CLB_WAV)
slt = feature.get_analyzer(dataset.SLT_WAV)
expected = kwiiyatta.align(clb, slt)
expected.f0 = slt.f0
feature.override_spectrum_power(expected, slt)
expected.aperiodicity = slt.aperiodicity
expected.mel_cepstrum = None
actual = kwiiyatta.analyze_wav(result_file)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, actual)
check.round_equal(0.10, f0_diff)
check.round_equal(0.36, spec_diff)
check.round_equal(0.076, ape_diff)
check.round_equal(0.081, mcep_diff)
def test_voice_resynthesis_carrier(check, tmpdir):
result_root = pathlib.Path(tmpdir)
sys.argv = [
sys.argv[0],
str(dataset.CLB_WAV), "--result-dir",
str(result_root), "--mcep", "--mcep-order", "48", "--carrier",
str(dataset.SLT_WAV)
]
rv.main()
result_file = result_root / 'arctic_a0001.wav'
assert result_file.is_file()
clb = feature.get_analyzer(dataset.CLB_WAV)
slt = feature.get_analyzer(dataset.SLT_WAV)
expected = kwiiyatta.align(clb, slt)
expected.f0 = slt.f0
actual = kwiiyatta.analyze_wav(result_file)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, actual)
check.round_equal(0.093, f0_diff)
check.round_equal(0.23, spec_diff)
check.round_equal(0.093, ape_diff)
check.round_equal(0.060, mcep_diff)
def test_voice_conversion(tmpdir, setup_func, target_fs, test_fs):
tmp_path = pathlib.Path(tmpdir)
result_root = tmp_path / 'result'
src_dir = tmp_path / 'src'
src_dir.mkdir(exist_ok=True)
setup_func(src_dir)
sys.argv = \
[
sys.argv[0],
'--source', str(src_dir),
'--target', str(dataset.get_dataset_path(dataset.SLT_DIR,
fs=target_fs)),
'--result-dir', str(result_root),
'--converter-seed', '0',
'--converter-components', '1',
'--max-files', '8',
str(dataset.get_wav_path(dataset.CLB_DIR/'arctic_a0009.wav',
fs=test_fs)),
]
np.random.seed(0)
cv.main()
assert (result_root / 'arctic_a0009.diff.wav').is_file()
assert (result_root / 'arctic_a0009.synth.wav').is_file()
expected = make_expected_feature('arctic_a0009.wav', fs=test_fs)
act_diff = kwiiyatta.analyze_wav(result_root / 'arctic_a0009.diff.wav')
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, act_diff)
assert_any.between(0.057, f0_diff, 0.092)
assert_any.between(0.46, spec_diff, 0.54)
assert_any.between(0.042, ape_diff, 0.049)
assert_any.between(0.077, mcep_diff, 0.11)
act_synth = kwiiyatta.analyze_wav(result_root / 'arctic_a0009.synth.wav')
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, act_synth)
assert_any.between(0.10, f0_diff, 0.12)
assert_any.between(0.47, spec_diff, 0.52)
assert_any.between(0.073, ape_diff, 0.095)
assert_any.between(0.078, mcep_diff, 0.11)
def test_analyze_difffile(check):
a1 = feature.get_analyzer(dataset.CLB_WAV)
a2 = feature.get_analyzer(dataset.CLB_WAV2)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(a1, a2, strict=False)
check.round_equal(0.63, f0_diff)
check.round_equal(1.0, spec_diff)
check.round_equal(0.49, ape_diff)
check.round_equal(0.27, mcep_diff)
def test_reanalyze(wavfile, dtype, fs, frame_period):
a1 = feature.get_analyzer(dataset.get_wav_path(wavfile, dtype=dtype,
fs=fs),
frame_period=frame_period)
assert a1.fs == fs
analyzer_wav = a1.synthesize()
feature_wav = kwiiyatta.feature(a1).synthesize()
assert analyzer_wav.fs == feature_wav.fs
assert (analyzer_wav.data == feature_wav.data).all()
a2 = kwiiyatta.Analyzer(analyzer_wav, frame_period=frame_period)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(a1, a2)
assert_any.between(0.052, f0_diff, 0.094)
assert_any.between(0.20, spec_diff, 0.22)
assert_any.between(0.063, ape_diff, 0.096)
assert_any.between(0.030, mcep_diff, 0.055)
def test_reshape(check):
from kwiiyatta.vocoder.world import WorldAnalyzer
a1 = kwiiyatta.analyze_wav(dataset.CLB_WAV)
a2 = WorldAnalyzer.load_wav(dataset.CLB_WAV)
fft_size = (a1.spectrum_len - 1) * 2 * 2
a2.extract_spectrum_envelope(fft_size=fft_size)
a2.extract_aperiodicity(fft_size=fft_size)
assert a1.spectrum_len != a2.spectrum_len
f2_r = kwiiyatta.reshape(a2, a1.spectrum_len)
assert f2_r.spectrum_len == a1.spectrum_len
f2 = kwiiyatta.feature(a2)
assert f2.spectrum_len != f2_r.spectrum_len
assert (feature.calc_powered_diff(
f2_r.spectrum_envelope,
f2.reshaped_spectrum_envelope(a1.spectrum_len)) == 0)
assert (feature.calc_diff(f2_r.aperiodicity,
f2.reshaped_aperiodicity(a1.spectrum_len)) == 0)
_, spec_diff, ape_diff, mcep_diff = feature.calc_feature_diffs(a1, f2_r)
check.round_equal(0.0025, spec_diff)
check.round_equal(0.00087, ape_diff)
check.round_equal(0.0012, mcep_diff)
a1._spectrum_envelope = None
a1._aperiodicity = None
spec_diff = feature.calc_powered_diff(
a2.spectrum_envelope, a1.reshaped_spectrum_envelope(f2.spectrum_len))
check.round_equal(0.0038, spec_diff)
ape_diff = feature.calc_diff(a2.aperiodicity,
a1.reshaped_aperiodicity(f2.spectrum_len))
check.round_equal(0.00088, ape_diff)
f1 = kwiiyatta.feature(a1)
f1.extract_mel_cepstrum()
f1.spectrum_envelope = None
spec_diff = feature.calc_powered_diff(
a2.spectrum_envelope, f1.reshaped_spectrum_envelope(a2.spectrum_len))
check.round_equal(0.090, spec_diff)
def test_voice_resynthesis(tmpdir, check):
result_root = pathlib.Path(tmpdir)
sys.argv = [
sys.argv[0],
"--result-dir",
str(result_root),
str(dataset.CLB_WAV),
]
rv.main()
result_file = result_root / 'arctic_a0001.wav'
assert result_file.is_file()
expected = kwiiyatta.analyze_wav(dataset.CLB_WAV)
actual = kwiiyatta.analyze_wav(result_file)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(expected, actual)
check.round_equal(0.079, f0_diff)
check.round_equal(0.20, spec_diff)
check.round_equal(0.073, ape_diff)
check.round_equal(0.054, mcep_diff)
def test_resample_up(fs1, fs2, wavfile, frame_period):
np.random.seed(0)
if fs1 < fs2:
fs1, fs2 = fs2, fs1
a1 = feature.get_analyzer(dataset.get_wav_path(wavfile, fs=fs1),
frame_period=frame_period)
a2 = feature.get_analyzer(dataset.get_wav_path(wavfile, fs=fs2),
frame_period=frame_period)
a2_r = kwiiyatta.resample(a2, fs1)
a2._spectrum_envelope = None
a2._aperiodicity = None
a2._mel_cepstrum.data = None
assert a1.fs == a2_r.fs
assert feature.calc_diff(a2_r.f0, a2.f0) == 0
assert_any.between(
1.7e-8,
feature.calc_powered_diff(a2_r.spectrum_envelope,
a2.resample_spectrum_envelope(a2_r.fs)),
1.4e-7)
assert (feature.calc_diff(a2_r.aperiodicity,
a2.resample_aperiodicity(a2_r.fs)) == 0)
assert_any.between(0.0009,
feature.calc_diff(
a2_r.mel_cepstrum.data,
a2.resample_mel_cepstrum(a2_r.fs).data),
0.004,
sig_dig=1)
assert a2.mel_cepstrum.order == a2_r.mel_cepstrum.order
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(a1, a2_r)
assert_any.between(0.0012, f0_diff, 0.014)
assert_any.between(0.0015, spec_diff, 0.0068)
assert_any.between(0.039, ape_diff, 0.20)
assert_any.between(0.10, mcep_diff, 0.36)
a2_r_wav = a2_r.synthesize()
a2_r_s = kwiiyatta.Analyzer(a2_r_wav, frame_period=frame_period)
f0_diff, spec_diff, ape_diff, mcep_diff = \
feature.calc_feature_diffs(a1, a2_r_s)
assert_any.between(0.050, f0_diff, 0.11)
assert_any.between(0.20, spec_diff, 0.23)
assert_any.between(0.065, ape_diff, 0.32)
assert_any.between(0.047, mcep_diff, 0.16)
f2 = kwiiyatta.feature(a2)
f2.extract_mel_cepstrum()
f2.spectrum_envelope = None
f2_mcep_r = f2.resample_mel_cepstrum(a1.fs)
mcep_diff = feature.calc_diff(a1.mel_cepstrum.data, f2_mcep_r.data)
assert_any.between(0.10, mcep_diff, 0.36)
a2_mcep_r = kwiiyatta.resample(a2.mel_cepstrum, a1.fs)
assert_any.between(0.0009,
feature.calc_diff(a2_mcep_r.data, f2_mcep_r.data),
0.004,
sig_dig=1)
frame_fs2 = a1.spectrum_envelope.shape[1] * fs2 // a1.fs
spec_diff = feature.calc_powered_diff(
a1.spectrum_envelope[:, :frame_fs2],
a2_r.spectrum_envelope[:, :frame_fs2])
assert_any.between(0.00012, spec_diff, 0.55)