video-dubbing-3min / TTS /tests /aux_tests /test_numpy_transforms.py
artificialguybr's picture
Upload 659 files
46a75d7
raw
history blame
4.36 kB
import math
import os
import unittest
from dataclasses import dataclass
import librosa
import numpy as np
from coqpit import Coqpit
from tests import get_tests_input_path, get_tests_output_path, get_tests_path
from TTS.utils.audio import numpy_transforms as np_transforms
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)
# pylint: disable=no-self-use
class TestNumpyTransforms(unittest.TestCase):
def setUp(self) -> None:
@dataclass
class AudioConfig(Coqpit):
sample_rate: int = 22050
fft_size: int = 1024
num_mels: int = 256
mel_fmax: int = 1800
mel_fmin: int = 0
hop_length: int = 256
win_length: int = 1024
pitch_fmax: int = 640
pitch_fmin: int = 1
trim_db: int = -1
min_silence_sec: float = 0.01
gain: float = 1.0
base: float = 10.0
self.config = AudioConfig()
self.sample_wav, _ = librosa.load(WAV_FILE, sr=self.config.sample_rate)
def test_build_mel_basis(self):
"""Check if the mel basis is correctly built"""
print(" > Testing mel basis building.")
mel_basis = np_transforms.build_mel_basis(**self.config)
self.assertEqual(mel_basis.shape, (self.config.num_mels, self.config.fft_size // 2 + 1))
def test_millisec_to_length(self):
"""Check if the conversion from milliseconds to length is correct"""
print(" > Testing millisec to length conversion.")
win_len, hop_len = np_transforms.millisec_to_length(
frame_length_ms=1000, frame_shift_ms=12.5, sample_rate=self.config.sample_rate
)
self.assertEqual(hop_len, int(12.5 / 1000.0 * self.config.sample_rate))
self.assertEqual(win_len, self.config.sample_rate)
def test_amplitude_db_conversion(self):
di = np.random.rand(11)
o1 = np_transforms.amp_to_db(x=di, gain=1.0, base=10)
o2 = np_transforms.db_to_amp(x=o1, gain=1.0, base=10)
np.testing.assert_almost_equal(di, o2, decimal=5)
def test_preemphasis_deemphasis(self):
di = np.random.rand(11)
o1 = np_transforms.preemphasis(x=di, coeff=0.95)
o2 = np_transforms.deemphasis(x=o1, coeff=0.95)
np.testing.assert_almost_equal(di, o2, decimal=5)
def test_spec_to_mel(self):
mel_basis = np_transforms.build_mel_basis(**self.config)
spec = np.random.rand(self.config.fft_size // 2 + 1, 20) # [C, T]
mel = np_transforms.spec_to_mel(spec=spec, mel_basis=mel_basis)
self.assertEqual(mel.shape, (self.config.num_mels, 20))
def mel_to_spec(self):
mel_basis = np_transforms.build_mel_basis(**self.config)
mel = np.random.rand(self.config.num_mels, 20) # [C, T]
spec = np_transforms.mel_to_spec(mel=mel, mel_basis=mel_basis)
self.assertEqual(spec.shape, (self.config.fft_size // 2 + 1, 20))
def test_wav_to_spec(self):
spec = np_transforms.wav_to_spec(wav=self.sample_wav, **self.config)
self.assertEqual(
spec.shape, (self.config.fft_size // 2 + 1, math.ceil(self.sample_wav.shape[0] / self.config.hop_length))
)
def test_wav_to_mel(self):
mel_basis = np_transforms.build_mel_basis(**self.config)
mel = np_transforms.wav_to_mel(wav=self.sample_wav, mel_basis=mel_basis, **self.config)
self.assertEqual(
mel.shape, (self.config.num_mels, math.ceil(self.sample_wav.shape[0] / self.config.hop_length))
)
def test_compute_f0(self):
pitch = np_transforms.compute_f0(x=self.sample_wav, **self.config)
mel_basis = np_transforms.build_mel_basis(**self.config)
mel = np_transforms.wav_to_mel(wav=self.sample_wav, mel_basis=mel_basis, **self.config)
assert pitch.shape[0] == mel.shape[1]
def test_load_wav(self):
wav = np_transforms.load_wav(filename=WAV_FILE, resample=False, sample_rate=22050)
wav_resample = np_transforms.load_wav(filename=WAV_FILE, resample=True, sample_rate=16000)
self.assertEqual(wav.shape, (self.sample_wav.shape[0],))
self.assertNotEqual(wav_resample.shape, (self.sample_wav.shape[0],))