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()
