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'])