def test_read_samples(self):
path = resources.sample_wav_file('wav_1.wav')
track = tracks.FileTrack('wav', path)
issuer = issuers.Issuer('toni')
utt = tracks.Utterance('t', track, issuer=issuer, start=1.0, end=2.30)
l1 = annotations.Label('a', 0.15, 0.448)
l2 = annotations.Label('a', 0.5, 0.73)
ll = annotations.LabelList(labels=[l1, l2])
utt.set_label_list(ll)
expected, __ = librosa.core.load(path,
sr=None,
offset=1.15,
duration=0.298)
assert np.array_equal(l1.read_samples(), expected)
expected, __ = librosa.core.load(path,
sr=None,
offset=1.5,
duration=1.73 - 1.5)
print(expected.shape)
print(l2.read_samples().shape)
assert np.array_equal(l2.read_samples(), expected)
def test_validate_returns_part_of_overlapping_label(self):
ds = resources.create_single_label_corpus()
utt4_ll = annotations.LabelList(idx='default',
labels=[
annotations.Label('a',
start=0.0,
end=9.0),
annotations.Label('b',
start=9.0,
end=13.0),
])
ds.utterances['utt-4'].set_label_list(utt4_ll)
utt6_ll = annotations.LabelList(idx='default',
labels=[
annotations.Label('a',
start=-2.0,
end=5.9),
annotations.Label('b',
start=5.9,
end=14.7),
])
ds.utterances['utt-6'].set_label_list(utt6_ll)
val = validation.LabelOverflowValidator('default')
result = val.validate(ds)
assert not result.passed
assert set(result.overflow_segments.keys()) == {'utt-4', 'utt-6'}
assert result.overflow_segments['utt-4'] == [(10.0, 13.0, 'b')]
assert result.overflow_segments['utt-6'] == [(-2.0, 0.0, 'a')]
def test_validate(self):
ds = resources.create_single_label_corpus()
utt4_ll = annotations.LabelList(idx='default',
labels=[
annotations.Label('a',
start=0.0,
end=1.44),
annotations.Label('a',
start=1.89,
end=10.0),
])
ds.utterances['utt-4'].set_label_list(utt4_ll)
utt6_ll = annotations.LabelList(idx='default',
labels=[
annotations.Label('a',
start=1.33,
end=5.9),
annotations.Label('a',
start=5.9,
end=14.7),
])
ds.utterances['utt-6'].set_label_list(utt6_ll)
val = validation.LabelCoverageValidator('default')
result = val.validate(ds)
assert not result.passed
assert set(result.uncovered_segments.keys()) == {'utt-4', 'utt-6'}
assert result.uncovered_segments['utt-4'] == [(1.44, 1.89)]
assert result.uncovered_segments['utt-6'] == [(0.0, 1.33),
(14.7, 15.0)]
def test_split(self):
ll_1 = annotations.LabelList('phones', labels=[
annotations.Label('alpha', start=0.0, end=30.0)
])
ll_2 = annotations.LabelList('words', labels=[
annotations.Label('b', start=0.0, end=30.0)
])
utt = tracks.Utterance('utt-1', 'track-x', start=0.0, end=40.0, label_lists=[ll_1, ll_2])
res = utt.split([14.0, 29.5])
assert len(res) == 3
assert res[0].start == 0.0
assert res[0].end == 14.0
assert 'phones' in res[0].label_lists.keys()
assert 'words' in res[0].label_lists.keys()
assert res[1].start == 14.0
assert res[1].end == 29.5
assert 'phones' in res[1].label_lists.keys()
assert 'words' in res[1].label_lists.keys()
assert res[2].start == 29.5
assert res[2].end == 40.0
assert 'phones' in res[2].label_lists.keys()
assert 'words' in res[2].label_lists.keys()
def test_encode_label_ends_at_utterance_end(self):
track = tracks.FileTrack('file1',
resources.sample_wav_file('med_len.wav'))
utt = tracks.Utterance('utt1', track, start=3, end=14)
ll = annotations.LabelList(labels=[
annotations.Label('speech', 0, 4),
annotations.Label('music', 4, 9),
annotations.Label('speech', 9, float('inf')),
])
utt.set_label_list(ll)
enc = encoding.FrameHotEncoder(['music', 'speech', 'noise'],
'default',
frame_settings=units.FrameSettings(
32000, 16000),
sr=16000)
actual = enc.encode_utterance(utt)
expected = np.array([
[0, 1, 0],
[0, 1, 0],
[0, 1, 0],
[1, 1, 0],
[1, 0, 0],
[1, 0, 0],
[1, 0, 0],
[1, 0, 0],
[1, 1, 0],
[0, 1, 0],
]).astype(np.float32)
assert np.array_equal(expected, actual)
def test_ordering_both_ref_none(self):
pair_a = alignment.LabelPair(
None, annotations.Label('a2', start=1.66, end=1.92))
pair_b = alignment.LabelPair(
None, annotations.Label('b2', start=1.65, end=1.92))
assert pair_b < pair_a
def test_read_label_list_de(self):
path = os.path.join(os.path.dirname(__file__), 'audacity_labels_de.txt')
ll = audacity.read_label_list(path)
assert ll == annotations.LabelList(labels=[
annotations.Label('music', 43352.824046, 43525.837661),
annotations.Label('speech_male', 43512.446969, 43531.343483),
])
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_read_label_list_with_empty_value(self):
path = os.path.join(os.path.dirname(__file__), 'audacity_labels_empty_value.txt')
ll = audacity.read_label_list(path)
assert ll == annotations.LabelList(labels=[
annotations.Label('music', 1, 4),
annotations.Label('', 4, 7),
annotations.Label('speech_male', 7, 9),
])
def test_ordering_only_end_differs(self):
pair_a = alignment.LabelPair(
annotations.Label('a1', start=1.55, end=1.88),
annotations.Label('a2', start=1.66, end=1.92))
pair_b = alignment.LabelPair(
annotations.Label('b1', start=1.55, end=1.87),
annotations.Label('b2', start=1.66, end=1.92))
assert pair_b < pair_a
def test_align_insertion(self):
ref_ll = []
hyp_ll = [annotations.Label('y', 7.6, 15.2)]
result = alignment.FullMatchingAligner(0.1).align(ref_ll, hyp_ll)
assert result == [
alignment.LabelPair(None, annotations.Label('y', 7.6, 15.2))
]
def test_align_deletion(self):
ref_ll = [annotations.Label('a', 4.2, 8.5)]
hyp_ll = []
result = alignment.FullMatchingAligner(0.1).align(ref_ll, hyp_ll)
assert result == [
alignment.LabelPair(annotations.Label('a', 4.2, 8.5), None)
]
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_eq_ignores_label_list_relation(self):
a = annotations.Label('some label A', 1.0, 2.0)
b = annotations.Label('some label a', 1.0, 2.0)
al = annotations.LabelList(idx='one', labels=[a])
bl = annotations.LabelList(idx='another', labels=[b])
assert a.label_list == al
assert b.label_list == bl
assert a == b
def test_ordering(self):
pair_a = alignment.LabelPair(
annotations.Label('a1', start=1.55, end=1.88),
annotations.Label('a2', start=1.66, end=1.92))
pair_b = alignment.LabelPair(
annotations.Label('b1', start=1.59, end=1.88),
annotations.Label('b2', start=1.66, end=1.92))
assert pair_a < pair_b
def test_label_set_for_value(self, sample_outcome):
ls = sample_outcome.label_set_for_value('down')
expected = [
annotations.Label('down', start=10.35, end=11.12),
annotations.Label('down', start=39.28, end=40.0),
annotations.Label('down', start=31.20, end=33.4),
annotations.Label('down', start=39.28, end=40.0),
annotations.Label('down', start=28.20, end=33.4)
]
assert sorted(expected) == sorted(ls.labels)
def test_align_deletion(self):
lev = alignment.LevenshteinAligner()
ali = lev.align(
ll_with_values(['a', 'b', 'c']),
ll_with_values(['a', 'c'])
)
assert ali == [
alignment.LabelPair(annotations.Label('a'), annotations.Label('a')),
alignment.LabelPair(annotations.Label('b'), None),
alignment.LabelPair(annotations.Label('c'), annotations.Label('c')),
]
def test_align_empty_ref_returns_all_none(self):
lev = alignment.LevenshteinAligner()
ali = lev.align(
ll_with_values([]),
ll_with_values(['a', 'b', 'c'])
)
assert ali == [
alignment.LabelPair(None, annotations.Label('a')),
alignment.LabelPair(None, annotations.Label('b')),
alignment.LabelPair(None, annotations.Label('c')),
]
def corpus_with_more_labels():
""" Corpus with an extra label-list. """
corpus = resources.create_single_label_corpus()
corpus.utterances['utt-1'].set_label_list(
annotations.LabelList(idx='radio',
labels=[annotations.Label('alpha')]))
corpus.utterances['utt-2'].set_label_list(
annotations.LabelList(idx='radio',
labels=[annotations.Label('alpha')]))
corpus.utterances['utt-3'].set_label_list(
annotations.LabelList(idx='radio', labels=[annotations.Label('beta')]))
corpus.utterances['utt-4'].set_label_list(
annotations.LabelList(idx='radio', labels=[annotations.Label('beta')]))
corpus.utterances['utt-5'].set_label_list(
annotations.LabelList(idx='radio', labels=[annotations.Label('beta')]))
corpus.utterances['utt-6'].set_label_list(
annotations.LabelList(idx='radio', labels=[annotations.Label('beta')]))
corpus.utterances['utt-7'].set_label_list(
annotations.LabelList(idx='radio', labels=[annotations.Label('beta')]))
corpus.utterances['utt-8'].set_label_list(
annotations.LabelList(idx='radio', labels=[annotations.Label('beta')]))
return corpus
def test_align_empty_ref_returns_insertions(self):
ll_ref = []
ll_hyp = [annotations.Label('greasy', 1.4, 1.9)]
aligner = alignment.BipartiteMatchingAligner(
substitution_penalty=2,
non_overlap_penalty_weight=1
)
matches = aligner.align(ll_ref, ll_hyp)
assert matches == [
alignment.LabelPair(None, annotations.Label('greasy', 1.4, 1.9))
]
def ll_with_values(values):
ll = []
for value in values:
ll.append(annotations.Label(value))
return ll
def test_false_rejection_rate_with_no_occurences_returns_zero(self):
result = evaluator.KWSEvaluator().evaluate(
annotations.LabelList(labels=[]),
annotations.LabelList(
labels=[annotations.Label('four', 2.5, 3.0)]))
assert result.false_rejection_rate() == 0.0
def test_label_creation(self):
a = annotations.Label('value', 6.2, 8.9)
assert a.value == 'value'
assert a.start == 6.2
assert a.end == 8.9
assert len(a.meta) == 0
def read_labels(path, corpus):
for label_file in glob.glob(
os.path.join(path, '{}_*.txt'.format(LABEL_FILE_PREFIX))):
file_name = os.path.basename(label_file)
key = file_name[len('{}_'.format(LABEL_FILE_PREFIX)
):len(file_name) - len('.txt')]
utterance_labels = collections.defaultdict(list)
labels = textfile.read_separated_lines_generator(label_file,
separator=' ',
max_columns=4)
for record in labels:
label = record[3]
start = float(record[1])
end = float(record[2])
meta = None
meta_match = META_PATTERN.match(label)
if end == -1:
end = float('inf')
if meta_match is not None:
meta_json = meta_match.group(2)
meta = json.loads(meta_json)
label = meta_match.group(1)
utterance_labels[record[0]].append(
annotations.Label(label, start, end, meta=meta))
for utterance_idx, labels in utterance_labels.items():
ll = annotations.LabelList(idx=key, labels=labels)
corpus.utterances[utterance_idx].set_label_list(ll)
def generate_labels(n):
items = []
for i in range(n):
label = annotations.Label('label-{}'.format(i))
items.append(label)
return items
def test_align_empty_hypothesis(self):
ref = annotations.LabelList(labels=[
annotations.Label('b', 4, 8)
])
hyp = annotations.LabelList(labels=[
])
result = alignment.InvariantSegmentAligner().align(ref, hyp)
assert len(result) == 1
segment = result[0]
assert segment.start == 4
assert segment.end == 8
assert segment.ref == [annotations.Label('b', 4, 8)]
assert segment.hyp == []
def test_label_creation_with_info(self):
a = annotations.Label('value', 6.2, 8.9, meta={'something': 2})
assert a.value == 'value'
assert a.start == 6.2
assert a.end == 8.9
assert len(a.meta) == 1
assert a.meta['something'] == 2
def test_merge_corpus_label_lists(self):
main_corpus = resources.create_dataset()
merging_corpus = resources.create_multi_label_corpus()
main_corpus.merge_corpus(merging_corpus)
assert set(main_corpus.utterances['utt-2_1'].label_lists.keys()) == {
'default'
}
ll = main_corpus.utterances['utt-2_1'].label_lists['default']
assert ll == annotations.LabelList(labels=[
annotations.Label('music', 0, 5),
annotations.Label('speech', 5, 12),
annotations.Label('music', 13, 15)
])
def test_set_label_list(self):
ll_4 = annotations.LabelList(idx='delta', labels=[
annotations.Label('y', 0.0, 3.3),
annotations.Label('t', 3.8, 7.9)
])
self.utt.set_label_list(ll_4)
assert len(self.utt.label_lists) == 4
assert self.utt.label_lists['alpha'] == self.ll_1
assert self.utt.label_lists['bravo'] == self.ll_2
assert self.utt.label_lists['charlie'] == self.ll_3
assert self.utt.label_lists['delta'] == ll_4
assert self.ll_1.utterance == self.utt
assert self.ll_2.utterance == self.utt
assert self.ll_3.utterance == self.utt
assert ll_4.utterance == self.utt
