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import math |
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import os |
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import unittest |
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from dataclasses import dataclass |
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import librosa |
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import numpy as np |
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from coqpit import Coqpit |
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from tests import get_tests_input_path, get_tests_output_path, get_tests_path |
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from TTS.utils.audio import numpy_transforms as np_transforms |
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TESTS_PATH = get_tests_path() |
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OUT_PATH = os.path.join(get_tests_output_path(), "audio_tests") |
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WAV_FILE = os.path.join(get_tests_input_path(), "example_1.wav") |
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os.makedirs(OUT_PATH, exist_ok=True) |
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class TestNumpyTransforms(unittest.TestCase): |
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def setUp(self) -> None: |
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@dataclass |
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class AudioConfig(Coqpit): |
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sample_rate: int = 22050 |
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fft_size: int = 1024 |
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num_mels: int = 256 |
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mel_fmax: int = 1800 |
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mel_fmin: int = 0 |
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hop_length: int = 256 |
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win_length: int = 1024 |
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pitch_fmax: int = 640 |
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pitch_fmin: int = 1 |
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trim_db: int = -1 |
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min_silence_sec: float = 0.01 |
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gain: float = 1.0 |
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base: float = 10.0 |
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self.config = AudioConfig() |
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self.sample_wav, _ = librosa.load(WAV_FILE, sr=self.config.sample_rate) |
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def test_build_mel_basis(self): |
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"""Check if the mel basis is correctly built""" |
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print(" > Testing mel basis building.") |
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mel_basis = np_transforms.build_mel_basis(**self.config) |
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self.assertEqual(mel_basis.shape, (self.config.num_mels, self.config.fft_size // 2 + 1)) |
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def test_millisec_to_length(self): |
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"""Check if the conversion from milliseconds to length is correct""" |
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print(" > Testing millisec to length conversion.") |
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win_len, hop_len = np_transforms.millisec_to_length( |
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frame_length_ms=1000, frame_shift_ms=12.5, sample_rate=self.config.sample_rate |
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) |
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self.assertEqual(hop_len, int(12.5 / 1000.0 * self.config.sample_rate)) |
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self.assertEqual(win_len, self.config.sample_rate) |
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def test_amplitude_db_conversion(self): |
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di = np.random.rand(11) |
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o1 = np_transforms.amp_to_db(x=di, gain=1.0, base=10) |
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o2 = np_transforms.db_to_amp(x=o1, gain=1.0, base=10) |
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np.testing.assert_almost_equal(di, o2, decimal=5) |
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def test_preemphasis_deemphasis(self): |
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di = np.random.rand(11) |
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o1 = np_transforms.preemphasis(x=di, coeff=0.95) |
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o2 = np_transforms.deemphasis(x=o1, coeff=0.95) |
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np.testing.assert_almost_equal(di, o2, decimal=5) |
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def test_spec_to_mel(self): |
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mel_basis = np_transforms.build_mel_basis(**self.config) |
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spec = np.random.rand(self.config.fft_size // 2 + 1, 20) |
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mel = np_transforms.spec_to_mel(spec=spec, mel_basis=mel_basis) |
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self.assertEqual(mel.shape, (self.config.num_mels, 20)) |
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def mel_to_spec(self): |
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mel_basis = np_transforms.build_mel_basis(**self.config) |
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mel = np.random.rand(self.config.num_mels, 20) |
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spec = np_transforms.mel_to_spec(mel=mel, mel_basis=mel_basis) |
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self.assertEqual(spec.shape, (self.config.fft_size // 2 + 1, 20)) |
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def test_wav_to_spec(self): |
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spec = np_transforms.wav_to_spec(wav=self.sample_wav, **self.config) |
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self.assertEqual( |
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spec.shape, (self.config.fft_size // 2 + 1, math.ceil(self.sample_wav.shape[0] / self.config.hop_length)) |
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) |
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def test_wav_to_mel(self): |
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mel_basis = np_transforms.build_mel_basis(**self.config) |
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mel = np_transforms.wav_to_mel(wav=self.sample_wav, mel_basis=mel_basis, **self.config) |
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self.assertEqual( |
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mel.shape, (self.config.num_mels, math.ceil(self.sample_wav.shape[0] / self.config.hop_length)) |
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) |
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def test_compute_f0(self): |
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pitch = np_transforms.compute_f0(x=self.sample_wav, **self.config) |
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mel_basis = np_transforms.build_mel_basis(**self.config) |
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mel = np_transforms.wav_to_mel(wav=self.sample_wav, mel_basis=mel_basis, **self.config) |
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assert pitch.shape[0] == mel.shape[1] |
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def test_load_wav(self): |
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wav = np_transforms.load_wav(filename=WAV_FILE, resample=False, sample_rate=22050) |
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wav_resample = np_transforms.load_wav(filename=WAV_FILE, resample=True, sample_rate=16000) |
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self.assertEqual(wav.shape, (self.sample_wav.shape[0],)) |
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self.assertNotEqual(wav_resample.shape, (self.sample_wav.shape[0],)) |
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