def test_mixed_cut_audio_mask(self): cut = MonoCut( "cut", start=0, duration=2, channel=0, recording=Mock(sampling_rate=16000) ) mixed_cut = cut.append(cut) mask = mixed_cut.supervisions_audio_mask() assert mask.sum() == 0
def test_mixed_cut_audio_mask(self, supervisions): cut = MonoCut( "cut", start=0, duration=2, channel=0, recording=Mock(sampling_rate=16000), supervisions=supervisions, ) mixed_cut = cut.append(cut) mask = mixed_cut.supervisions_audio_mask() ones = np.index_exp[ list( chain( range(0, 8000), range(9600, 12800), range(32000, 40000), range(41600, 44800), ) ) ] zeros = np.index_exp[ list( chain( range(8000, 9600), range(12800, 32000), range(40000, 41600), range(44800, 64000), ) ) ] assert (mask[ones] == 1).all() assert (mask[zeros] == 0).all()
def test_mixed_cut_features_mask(self): cut = MonoCut('cut', start=0, duration=2, channel=0, features=Mock(sampling_rate=16000, frame_shift=0.01)) mixed_cut = cut.append(cut) mask = mixed_cut.supervisions_feature_mask() assert mask.sum() == 0
def test_mixed_cut_features_mask(self, supervisions): cut = MonoCut('cut', start=0, duration=2, channel=0, features=Mock(sampling_rate=16000, frame_shift=0.01), supervisions=supervisions) mixed_cut = cut.append(cut) mask = mixed_cut.supervisions_feature_mask() ones = np.index_exp[list( chain(range(0, 50), range(60, 80), range(200, 250), range(260, 280)))] zeros = np.index_exp[list( chain(range(50, 60), range(80, 200), range(250, 260), range(280, 400)))] assert (mask[ones] == 1).all() assert (mask[zeros] == 0).all()