def test_fbank(self):
"""Test Fbank using 16kHz && 8kHz wav."""
wav_path_16k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln.wav"))
wav_path_8k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/english.wav"))
with self.session():
# value test
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path_16k)
fbank = Fbank.params({"delta_delta": False}).instantiate()
fbank_test = fbank(input_data, sample_rate)
real_fank_feats = np.array([
[3.768338, 4.946218, 6.289874, 6.330853, 6.761764, 6.884573],
[3.803553, 5.450971, 6.547878, 5.796172, 6.397846, 7.242926],
])
# self.assertAllClose(np.squeeze(fbank_test.eval()[0:2, 0:6, 0]),
# real_fank_feats, rtol=1e-05, atol=1e-05)
if tf.executing_eagerly():
print(fbank_test.numpy()[0:2, 0:6, 0])
else:
print(fbank_test.eval()[0:2, 0:6, 0])
count = 1
for wav_file in [wav_path_8k, wav_path_16k]:
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_file)
if tf.executing_eagerly():
print(wav_file, sample_rate.numpy())
else:
print(wav_file, sample_rate.eval())
conf = {
"delta_delta": True,
"lower_frequency_limit": 100,
"upper_frequency_limit": 0,
}
fbank = Fbank.params(conf).instantiate()
fbank_test = fbank(input_data, sample_rate)
if tf.executing_eagerly():
print(fbank_test.numpy())
else:
print(fbank_test.eval())
print(fbank.num_channels())
conf = {
"delta_delta": False,
"lower_frequency_limit": 100,
"upper_frequency_limit": 0,
}
fbank = Fbank.params(conf).instantiate()
fbank_test = fbank(input_data, sample_rate)
print(fbank_test)
print(fbank.num_channels())
count += 1
del read_wav
del fbank
def test_framepow(self):
wav_path_16k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln.wav"))
with self.session():
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path_16k)
config = {"snip_edges": 1}
framepow = Framepow.params(config).instantiate()
framepow_test = framepow(input_data, sample_rate)
real_framepow_feats = np.array(
[9.819611, 9.328745, 9.247337, 9.26451, 9.266059])
if tf.executing_eagerly():
self.assertAllClose(
framepow_test.numpy()[0:5],
real_framepow_feats,
rtol=1e-05,
atol=1e-05,
)
print(framepow_test.numpy()[0:5])
else:
self.assertAllClose(
framepow_test.eval()[0:5],
real_framepow_feats,
rtol=1e-05,
atol=1e-05,
)
print(framepow_test.eval()[0:5])
def test_mel_spectrum(self):
# 16kHz test
wav_path_16k = str(
Path(os.environ['MAIN_ROOT']).joinpath('examples/sm1_cln.wav'))
with self.session():
# value test
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path_16k)
config = {
'type': 'MelSpectrum',
'window_type': 'hann',
'upper_frequency_limit': 7600,
'filterbank_channel_count': 80,
'lower_frequency_limit': 80,
'dither': 0.0,
'window_length': 0.025,
'frame_length': 0.010,
'remove_dc_offset': False,
'preEph_coeff': 0.0,
'output_type': 3
}
mel_spectrum = MelSpectrum.params(config).instantiate()
mel_spectrum_test = mel_spectrum(input_data, sample_rate)
if tf.executing_eagerly():
print(mel_spectrum_test.numpy()[0:2, 0:10])
else:
print(mel_spectrum_test.eval()[0:2, 0:10])
def test_write_wav(self):
wav_path = str(Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln.wav"))
with self.cached_session() as sess:
config = {"speed": 1.1}
read_wav = ReadWav.params(config).instantiate()
input_data, sample_rate = read_wav(wav_path)
write_wav = WriteWav.params().instantiate()
new_path = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln_resample.wav")
)
writewav_op = write_wav(new_path, input_data / 32768, sample_rate)
sess.run(writewav_op)
def test_spectrum(self):
"""Test Pitch using 16kHz && 8kHz wav."""
wav_path_16k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln.wav"))
wav_path_8k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/english.wav"))
with self.session():
for wav_file in [wav_path_16k]:
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_file)
pitch = Pitch.params({
"window_length": 0.025,
"soft_min_f0": 10.0
}).instantiate()
pitch_test = pitch(input_data, sample_rate)
if tf.executing_eagerly():
self.assertEqual(tf.rank(pitch_test).numpy(), 2)
else:
self.assertEqual(tf.rank(pitch_test).eval(), 2)
output_true = [
[-0.1366025, 143.8855],
[-0.0226383, 143.8855],
[-0.08464742, 143.8855],
[-0.08458386, 143.8855],
[-0.1208689, 143.8855],
]
if wav_file == wav_path_16k:
if tf.executing_eagerly():
print("Transform: ", pitch_test.numpy()[0:5, :])
print("kaldi:", output_true)
self.assertAllClose(
pitch_test.numpy()[0:5, :],
output_true,
rtol=1e-05,
atol=1e-05,
)
else:
print("Transform: ", pitch_test.eval())
print("kaldi:", output_true)
self.assertAllClose(
pitch_test.eval()[0:5, :],
output_true,
rtol=1e-05,
atol=1e-05,
)
def test_read_wav(self):
wav_path = str(Path(os.environ['MAIN_ROOT']).joinpath('examples/sm1_cln.wav'))
with self.session():
speed = 0.9
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path, speed)
audio_data_true, sample_rate_true = librosa.load(wav_path, sr=16000)
if (speed == 1.0):
if tf.executing_eagerly():
self.assertAllClose(input_data.numpy() / 32768, audio_data_true)
self.assertAllClose(sample_rate.numpy(), sample_rate_true)
else:
self.assertAllClose(input_data.eval() / 32768, audio_data_true)
self.assertAllClose(sample_rate.eval(), sample_rate_true)
def test_spectrum(self):
wav_path_16k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln.wav"))
wav_path_8k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/english.wav"))
with self.session():
for wav_file in [wav_path_8k, wav_path_16k]:
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_file)
spectrum = Spectrum.params({
"window_length": 0.025,
"dither": 0.0
}).instantiate()
spectrum_test = spectrum(input_data, sample_rate)
output_true = np.array([
[9.819611, 2.84503, 3.660894, 2.7779, 1.212233],
[9.328745, 2.553949, 3.276319, 3.000918, 2.499342],
])
if tf.executing_eagerly():
self.assertEqual(tf.rank(spectrum_test).numpy(), 2)
else:
self.assertEqual(tf.rank(spectrum_test).eval(), 2)
if wav_file == wav_path_16k:
if tf.executing_eagerly():
self.assertAllClose(
spectrum_test.numpy()[0:2, 0:5],
output_true,
rtol=1e-05,
atol=1e-05,
)
else:
self.assertAllClose(
spectrum_test.eval()[0:2, 0:5],
output_true,
rtol=1e-05,
atol=1e-05,
)
def test_FbankPitch(self):
wav_path = str(
Path(os.environ['MAIN_ROOT']).joinpath('examples/sm1_cln.wav'))
with self.session():
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path)
config = {
'window_length': 0.025,
'output_type': 1,
'frame_length': 0.010,
'dither': 0.0
}
fbank_pitch = FbankPitch.params(config).instantiate()
fbank_pitch_test = fbank_pitch(input_data, sample_rate)
if tf.executing_eagerly():
self.assertEqual(tf.rank(fbank_pitch_test).numpy(), 3)
print(fbank_pitch_test.numpy()[0:2, :, 0])
else:
self.assertEqual(tf.rank(fbank_pitch_test).eval(), 3)
print(fbank_pitch_test.eval()[0:2, :, 0])
def test_mfcc(self):
wav_path_16k = str(
Path(os.environ["MAIN_ROOT"]).joinpath("examples/sm1_cln.wav"))
with self.session():
read_wav = ReadWav.params().instantiate()
input_data, sample_rate = read_wav(wav_path_16k)
config = {"use_energy": True}
mfcc = Mfcc.params(config).instantiate()
mfcc_test = mfcc(input_data, sample_rate)
real_mfcc_feats = np.array([
[
9.819611, -30.58736, -7.088838, -10.67966, -1.646479,
-4.36086
],
[
9.328745, -30.73371, -6.128432, -7.930599, 3.208357,
-1.086456
],
])
if tf.executing_eagerly():
self.assertAllClose(
mfcc_test.numpy()[0, 0:2, 0:6],
real_mfcc_feats,
rtol=1e-05,
atol=1e-05,
)
else:
self.assertAllClose(
mfcc_test.eval()[0, 0:2, 0:6],
real_mfcc_feats,
rtol=1e-05,
atol=1e-05,
)
