File size: 4,071 Bytes
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import unittest
from pathlib import Path
import numpy as np
import soundfile as sf
from infer.cover_pipeline import CoverPipeline
def _rms(audio: np.ndarray) -> float:
return float(np.sqrt(np.mean(np.square(audio)) + 1e-12))
def _preemphasis_rms(audio: np.ndarray) -> float:
audio = np.asarray(audio, dtype=np.float32).reshape(-1)
if audio.size == 0:
return 0.0
residual = np.empty_like(audio)
residual[0] = audio[0]
residual[1:] = audio[1:] - 0.97 * audio[:-1]
return _rms(residual)
def _fade(length: int) -> np.ndarray:
env = np.ones(length, dtype=np.float32)
ramp = max(1, min(length // 4, 512))
env[:ramp] = np.linspace(0.0, 1.0, ramp, dtype=np.float32)
env[-ramp:] = np.linspace(1.0, 0.0, ramp, dtype=np.float32)
return env
class EchoTailGateTests(unittest.TestCase):
def test_loud_echo_tail_is_suppressed_when_dereverb_removes_it(self):
sr = 48000
t = np.arange(int(2.4 * sr), dtype=np.float32) / sr
original = np.zeros_like(t)
dereverbed = np.zeros_like(t)
direct_mask = (t >= 0.20) & (t < 0.72)
echo_mask = (t >= 1.16) & (t < 1.68)
direct = 0.24 * np.sin(2.0 * np.pi * 330.0 * t[direct_mask])
echo = 0.12 * np.sin(2.0 * np.pi * 330.0 * (t[echo_mask] - 0.96))
direct *= _fade(direct.size)
echo *= _fade(echo.size)
original[direct_mask] = direct
original[echo_mask] = echo
dereverbed[direct_mask] = direct
gain, gated_frames, total_frames = CoverPipeline._compute_echo_tail_sample_gain(
original=original,
dereverbed=dereverbed,
sr=sr,
)
direct_gain = gain[int(0.34 * sr): int(0.58 * sr)]
echo_gain = gain[int(1.28 * sr): int(1.54 * sr)]
self.assertGreater(total_frames, 0)
self.assertGreater(gated_frames, 0)
self.assertGreater(float(np.percentile(direct_gain, 5)), 0.85)
self.assertLess(
float(np.mean(echo_gain)),
0.55,
"loud echo tails should be reduced even when they are not quiet",
)
class BreathCleanupTests(unittest.TestCase):
def test_low_energy_recovery_breath_loses_tonal_hf_without_body_loss(self):
sr = 48000
t = np.arange(int(2.0 * sr), dtype=np.float32) / sr
source = np.zeros_like(t)
converted = np.zeros_like(t)
body = (t >= 0.25) & (t < 0.90)
breath = (t >= 1.15) & (t < 1.45)
source[body] = 0.15 * np.sin(2.0 * np.pi * 260.0 * t[body])
converted[body] = source[body]
breath_body = 0.012 * np.sin(2.0 * np.pi * 620.0 * t[breath])
breath_body *= _fade(breath_body.size)
source[breath] = breath_body
converted[breath] = breath_body + 0.009 * np.sin(2.0 * np.pi * 5200.0 * t[breath])
with tempfile.TemporaryDirectory() as tmp_dir:
tmp = Path(tmp_dir)
source_path = tmp / "source.wav"
converted_path = tmp / "converted.wav"
sf.write(source_path, source, sr)
sf.write(converted_path, converted, sr)
pipeline = CoverPipeline(device="cpu")
before, _ = sf.read(converted_path)
pipeline._apply_source_breath_cleanup(str(source_path), str(converted_path))
pipeline._apply_source_transition_cleanup(str(source_path), str(converted_path))
after, out_sr = sf.read(converted_path)
self.assertEqual(out_sr, sr)
before_breath = before[int(1.20 * sr): int(1.40 * sr)]
after_breath = after[int(1.20 * sr): int(1.40 * sr)]
before_body = before[int(0.36 * sr): int(0.76 * sr)]
after_body = after[int(0.36 * sr): int(0.76 * sr)]
self.assertLess(_preemphasis_rms(after_breath), _preemphasis_rms(before_breath) * 0.80)
self.assertGreater(_rms(after_body), _rms(before_body) * 0.96)
if __name__ == "__main__":
unittest.main()
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