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test_audio.py
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import os
import unittest
from tests import get_tests_input_path, get_tests_output_path, get_tests_path
from TTS.config import BaseAudioConfig
from TTS.utils.audio import AudioProcessor
TESTS_PATH = get_tests_path()
OUT_PATH = os.path.join(get_tests_output_path(), "audio_tests")
WAV_FILE = os.path.join(get_tests_input_path(), "example_1.wav")
os.makedirs(OUT_PATH, exist_ok=True)
conf = BaseAudioConfig(mel_fmax=8000)
# pylint: disable=protected-access
class TestAudio(unittest.TestCase):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.ap = AudioProcessor(**conf)
def test_audio_synthesis(self):
"""1. load wav
2. set normalization parameters
3. extract mel-spec
4. invert to wav and save the output
"""
print(" > Sanity check for the process wav -> mel -> wav")
def _test(max_norm, signal_norm, symmetric_norm, clip_norm):
self.ap.max_norm = max_norm
self.ap.signal_norm = signal_norm
self.ap.symmetric_norm = symmetric_norm
self.ap.clip_norm = clip_norm
wav = self.ap.load_wav(WAV_FILE)
mel = self.ap.melspectrogram(wav)
wav_ = self.ap.inv_melspectrogram(mel)
file_name = "/audio_test-melspec_max_norm_{}-signal_norm_{}-symmetric_{}-clip_norm_{}.wav".format(
max_norm, signal_norm, symmetric_norm, clip_norm
)
print(" | > Creating wav file at : ", file_name)
self.ap.save_wav(wav_, OUT_PATH + file_name)
# maxnorm = 1.0
_test(1.0, False, False, False)
_test(1.0, True, False, False)
_test(1.0, True, True, False)
_test(1.0, True, False, True)
_test(1.0, True, True, True)
# maxnorm = 4.0
_test(4.0, False, False, False)
_test(4.0, True, False, False)
_test(4.0, True, True, False)
_test(4.0, True, False, True)
_test(4.0, True, True, True)
def test_normalize(self):
"""Check normalization and denormalization for range values and consistency"""
print(" > Testing normalization and denormalization.")
wav = self.ap.load_wav(WAV_FILE)
wav = self.ap.sound_norm(wav) # normalize audio to get abetter normalization range below.
self.ap.signal_norm = False
x = self.ap.melspectrogram(wav)
x_old = x
self.ap.signal_norm = True
self.ap.symmetric_norm = False
self.ap.clip_norm = False
self.ap.max_norm = 4.0
x_norm = self.ap.normalize(x)
print(
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}"
)
assert (x_old - x).sum() == 0
# check value range
assert x_norm.max() <= self.ap.max_norm + 1, x_norm.max()
assert x_norm.min() >= 0 - 1, x_norm.min()
# check denorm.
x_ = self.ap.denormalize(x_norm)
assert (x - x_).sum() < 1e-3, (x - x_).mean()
self.ap.signal_norm = True
self.ap.symmetric_norm = False
self.ap.clip_norm = True
self.ap.max_norm = 4.0
x_norm = self.ap.normalize(x)
print(
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}"
)
assert (x_old - x).sum() == 0
# check value range
assert x_norm.max() <= self.ap.max_norm, x_norm.max()
assert x_norm.min() >= 0, x_norm.min()
# check denorm.
x_ = self.ap.denormalize(x_norm)
assert (x - x_).sum() < 1e-3, (x - x_).mean()
self.ap.signal_norm = True
self.ap.symmetric_norm = True
self.ap.clip_norm = False
self.ap.max_norm = 4.0
x_norm = self.ap.normalize(x)
print(
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}"
)
assert (x_old - x).sum() == 0
# check value range
assert x_norm.max() <= self.ap.max_norm + 1, x_norm.max()
assert x_norm.min() >= -self.ap.max_norm - 2, x_norm.min() # pylint: disable=invalid-unary-operand-type
assert x_norm.min() <= 0, x_norm.min()
# check denorm.
x_ = self.ap.denormalize(x_norm)
assert (x - x_).sum() < 1e-3, (x - x_).mean()
self.ap.signal_norm = True
self.ap.symmetric_norm = True
self.ap.clip_norm = True
self.ap.max_norm = 4.0
x_norm = self.ap.normalize(x)
print(
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}"
)
assert (x_old - x).sum() == 0
# check value range
assert x_norm.max() <= self.ap.max_norm, x_norm.max()
assert x_norm.min() >= -self.ap.max_norm, x_norm.min() # pylint: disable=invalid-unary-operand-type
assert x_norm.min() <= 0, x_norm.min()
# check denorm.
x_ = self.ap.denormalize(x_norm)
assert (x - x_).sum() < 1e-3, (x - x_).mean()
self.ap.signal_norm = True
self.ap.symmetric_norm = False
self.ap.max_norm = 1.0
x_norm = self.ap.normalize(x)
print(
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}"
)
assert (x_old - x).sum() == 0
assert x_norm.max() <= self.ap.max_norm, x_norm.max()
assert x_norm.min() >= 0, x_norm.min()
x_ = self.ap.denormalize(x_norm)
assert (x - x_).sum() < 1e-3
self.ap.signal_norm = True
self.ap.symmetric_norm = True
self.ap.max_norm = 1.0
x_norm = self.ap.normalize(x)
print(
f" > MaxNorm: {self.ap.max_norm}, ClipNorm:{self.ap.clip_norm}, SymmetricNorm:{self.ap.symmetric_norm}, SignalNorm:{self.ap.signal_norm} Range-> {x_norm.max()} -- {x_norm.min()}"
)
assert (x_old - x).sum() == 0
assert x_norm.max() <= self.ap.max_norm, x_norm.max()
assert x_norm.min() >= -self.ap.max_norm, x_norm.min() # pylint: disable=invalid-unary-operand-type
assert x_norm.min() < 0, x_norm.min()
x_ = self.ap.denormalize(x_norm)
assert (x - x_).sum() < 1e-3
def test_scaler(self):
scaler_stats_path = os.path.join(get_tests_input_path(), "scale_stats.npy")
conf.stats_path = scaler_stats_path
conf.preemphasis = 0.0
conf.do_trim_silence = True
conf.signal_norm = True
ap = AudioProcessor(**conf)
mel_mean, mel_std, linear_mean, linear_std, _ = ap.load_stats(scaler_stats_path)
ap.setup_scaler(mel_mean, mel_std, linear_mean, linear_std)
self.ap.signal_norm = False
self.ap.preemphasis = 0.0
# test scaler forward and backward transforms
wav = self.ap.load_wav(WAV_FILE)
mel_reference = self.ap.melspectrogram(wav)
mel_norm = ap.melspectrogram(wav)
mel_denorm = ap.denormalize(mel_norm)
assert abs(mel_reference - mel_denorm).max() < 1e-4