def test_vad_warning(self):
"""vad should throw a warning if input dimension is greater than 2"""
sample_rate = 41100
data = torch.rand(5, 5, sample_rate)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
T.Vad(sample_rate)(data)
assert len(w) == 1
data = torch.rand(5, sample_rate)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
T.Vad(sample_rate)(data)
assert len(w) == 0
data = torch.rand(sample_rate)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
T.Vad(sample_rate)(data)
assert len(w) == 0
def test_Vad(self):
filepath = common_utils.get_asset_path("vad-go-mono-32000.wav")
common_utils.set_audio_backend('default')
waveform, sample_rate = torchaudio.load(filepath)
self._assert_consistency(T.Vad(sample_rate=sample_rate), waveform)
def test_Vad(self):
filepath = common_utils.get_asset_path("vad-go-mono-32000.wav")
waveform, sample_rate = common_utils.load_wav(filepath)
self._assert_consistency(T.Vad(sample_rate=sample_rate), waveform)
def test_vad(self, filename):
path = get_asset_path(filename)
data, sample_rate = load_wav(path)
result = T.Vad(sample_rate)(data)
self.assert_sox_effect(result, path, ['vad'])
