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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.processor 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, pitch_fmax=640, pitch_fmin=1) | |
| # 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 | |
| def test_compute_f0(self): # pylint: disable=no-self-use | |
| ap = AudioProcessor(**conf) | |
| wav = ap.load_wav(WAV_FILE) | |
| pitch = ap.compute_f0(wav) | |
| mel = ap.melspectrogram(wav) | |
| assert pitch.shape[0] == mel.shape[1] | |