def test_cut_features_mask(self): cut = MonoCut( "cut", start=0, duration=2, channel=0, features=Mock(sampling_rate=16000, frame_shift=0.01, num_frames=2000), ) mask = cut.supervisions_feature_mask() assert mask.sum() == 0
def test_cut_features_mask(self, supervisions, alignment): cut = MonoCut( "cut", start=0, duration=2, channel=0, features=Mock(sampling_rate=16000, frame_shift=0.01, num_frames=2000), supervisions=supervisions, ) mask = cut.supervisions_feature_mask(use_alignment_if_exists=alignment) if alignment == "word": ones = np.index_exp[list(chain(range(0, 10), range(20, 40), range(60, 80)))] zeros = np.index_exp[ list(chain(range(10, 20), range(40, 60), range(80, 200))) ] else: ones = np.index_exp[list(chain(range(0, 50), range(60, 80)))] zeros = np.index_exp[list(chain(range(50, 60), range(80, 200)))] assert (mask[ones] == 1).all() assert (mask[zeros] == 0).all()