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()
