def test_equals(self):
seg_a = alignment.Segment(
0.0, 0.9, ref=[annotations.Label('a'),
annotations.Label('a')])
seg_b = alignment.Segment(
0.0, 0.9, ref=[annotations.Label('a'),
annotations.Label('a')])
assert seg_a == seg_b
def test_compare_multi_labels_returns_smaller_start_time(self):
seg_a = alignment.Segment(
0.0, 0.9, ref=[annotations.Label('a'),
annotations.Label('a')])
seg_b = alignment.Segment(
0.2, 0.8, ref=[annotations.Label('a'),
annotations.Label('a')])
assert seg_a < seg_b
def test_compare_multi_labels_with_same_times_returns_smaller_label_value(
self):
seg_a = alignment.Segment(
0.0, 1.0, ref=[annotations.Label('a'),
annotations.Label('a')])
seg_b = alignment.Segment(
0.0, 1.0, ref=[annotations.Label('a'),
annotations.Label('b')])
assert seg_a < seg_b
def test_create_from_segments():
segments = [
alignment.Segment(0, 4, annotations.Label('music', start=0, end=5),
annotations.Label('music', start=0, end=4)),
alignment.Segment(4, 5, annotations.Label('music', start=0, end=5),
annotations.Label('speech', start=4, end=6)),
alignment.Segment(5, 6, annotations.Label('speech', start=5, end=11),
annotations.Label('speech', start=4, end=6)),
alignment.Segment(6, 8, annotations.Label('speech', start=5, end=11),
None),
alignment.Segment(8, 11, annotations.Label('speech', start=5, end=11),
annotations.Label('mix', start=8, end=16)),
alignment.Segment(11, 14, annotations.Label('mix', start=11, end=14),
annotations.Label('mix', start=8, end=16)),
alignment.Segment(14, 16, annotations.Label('speech', start=14,
end=19),
annotations.Label('mix', start=8, end=16)),
alignment.Segment(16, 19, annotations.Label('speech', start=14,
end=19),
annotations.Label('speech', start=16, end=21)),
alignment.Segment(19, 21, None,
annotations.Label('speech', start=16, end=21))
]
cnf = confusion.create_from_segments(segments)
assert cnf.correct == pytest.approx(11)
assert cnf.insertions == pytest.approx(2)
assert cnf.deletions == pytest.approx(2)
assert cnf.substitutions == pytest.approx(6)
assert cnf.substitutions_out == pytest.approx(6)
assert cnf.total == pytest.approx(19)
assert len(cnf.instances) == 3
assert cnf.instances['music'].correct == pytest.approx(4)
assert cnf.instances['music'].insertions == pytest.approx(0)
assert cnf.instances['music'].deletions == pytest.approx(0)
assert cnf.instances['music'].substitutions == pytest.approx(1)
assert cnf.instances['music'].substitutions_out == pytest.approx(0)
assert cnf.instances['music'].total == pytest.approx(5)
assert cnf.instances['speech'].correct == pytest.approx(4)
assert cnf.instances['speech'].insertions == pytest.approx(2)
assert cnf.instances['speech'].deletions == pytest.approx(2)
assert cnf.instances['speech'].substitutions == pytest.approx(5)
assert cnf.instances['speech'].substitutions_out == pytest.approx(1)
assert cnf.instances['speech'].total == pytest.approx(11)
assert cnf.instances['mix'].correct == pytest.approx(3)
assert cnf.instances['mix'].insertions == pytest.approx(0)
assert cnf.instances['mix'].deletions == pytest.approx(0)
assert cnf.instances['mix'].substitutions == pytest.approx(0)
assert cnf.instances['mix'].substitutions_out == pytest.approx(5)
assert cnf.instances['mix'].total == pytest.approx(3)
def test_evaluate_with_two_label_lists(
self, classification_ref_and_hyp_label_list):
ll_ref, ll_hyp = classification_ref_and_hyp_label_list
result = evaluator.SegmentEvaluator().evaluate(ll_ref, ll_hyp)
expected_segments = [
alignment.Segment(0, 4, annotations.Label('music', start=0, end=5),
annotations.Label('music', start=0, end=4)),
alignment.Segment(4, 5, annotations.Label('music', start=0, end=5),
annotations.Label('speech', start=4, end=6)),
alignment.Segment(5, 6, annotations.Label('speech',
start=5,
end=11),
annotations.Label('speech', start=4, end=6)),
alignment.Segment(6, 8, annotations.Label('speech',
start=5,
end=11), None),
alignment.Segment(8, 11,
annotations.Label('speech', start=5, end=11),
annotations.Label('mix', start=8, end=16)),
alignment.Segment(11, 14, annotations.Label('mix',
start=11,
end=14),
annotations.Label('mix', start=8, end=16)),
alignment.Segment(14, 16,
annotations.Label('speech', start=14, end=19),
annotations.Label('mix', start=8, end=16)),
alignment.Segment(16, 19,
annotations.Label('speech', start=14, end=19),
annotations.Label('speech', start=16, end=21)),
alignment.Segment(19, 21, None,
annotations.Label('speech', start=16, end=21))
]
assert isinstance(result, evaluator.SegmentEvaluation)
assert sorted(result.utt_to_segments[
evaluator.Evaluator.DEFAULT_UTT_IDX]) == sorted(expected_segments)
def test_compare_single_labels_returns_smaller_start_time(self):
seg_a = alignment.Segment(0.0, 0.9, ref=annotations.Label('a'))
seg_b = alignment.Segment(0.2, 0.7, ref=annotations.Label('a'))
assert seg_a < seg_b
def test_duration(self):
seg = alignment.Segment(0.8, 1.9)
assert seg.duration == pytest.approx(1.1)
def sample_confusion():
cnf = confusion.SegmentConfusion('music')
cnf.correct_segments = [
alignment.Segment(0, 3),
alignment.Segment(88, 103),
alignment.Segment(159.2, 193.1)
]
cnf.insertion_segments = [
alignment.Segment(8, 19),
alignment.Segment(55, 67.2)
]
cnf.deletion_segments = [
alignment.Segment(22, 28.2),
alignment.Segment(31, 38.2),
alignment.Segment(115, 124.9)
]
cnf.substitution_segments = {
'speech': [
alignment.Segment(44, 48.9),
alignment.Segment(198, 204.9)
],
'mix': [
alignment.Segment(133.4, 141.2)
]
}
cnf.substitution_out_segments = {
'speech': [
alignment.Segment(208.9, 210.2)
],
'mix': [
alignment.Segment(70.2, 79.78),
alignment.Segment(4, 7)
]
}
return cnf
