def _create_subviews(path, corpus):
""" Load the subviews based on testing_list.txt and validation_list.txt """
test_list_path = os.path.join(path, 'testing_list.txt')
dev_list_path = os.path.join(path, 'validation_list.txt')
test_list = textfile.read_separated_lines(test_list_path,
separator='/',
max_columns=2)
dev_list = textfile.read_separated_lines(dev_list_path,
separator='/',
max_columns=2)
test_set = set([
'{}_{}'.format(os.path.splitext(x[1])[0], x[0]) for x in test_list
])
dev_set = set([
'{}_{}'.format(os.path.splitext(x[1])[0], x[0]) for x in dev_list
])
inv_train_set = test_set.union(dev_set)
train_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs=inv_train_set, inverse=True)
train_view = subview.Subview(corpus, filter_criteria=train_filter)
corpus.import_subview('train', train_view)
dev_filter = subview.MatchingUtteranceIdxFilter(utterance_idxs=dev_set,
inverse=False)
dev_view = subview.Subview(corpus, filter_criteria=dev_filter)
corpus.import_subview('dev', dev_view)
test_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs=test_set, inverse=False)
test_view = subview.Subview(corpus, filter_criteria=test_filter)
corpus.import_subview('test', test_view)
def create_sample_dataset(temp_dir):
ds = audiomate.Corpus(str(temp_dir))
file_1_path = resources.sample_wav_file('wav_1.wav')
file_2_path = resources.sample_wav_file('wav_2.wav')
file_3_path = resources.get_resource_path(
['audio_formats', 'flac_1_16k_16b.flac'])
file_1 = ds.new_file(file_1_path, track_idx='wav_1')
file_2 = ds.new_file(file_2_path, track_idx='wav_2')
file_3 = ds.new_file(file_3_path, track_idx='wav_3')
issuer_1 = Speaker('spk-1', gender=Gender.MALE)
issuer_2 = Speaker('spk-2', gender=Gender.FEMALE)
issuer_3 = Issuer('spk-3')
ds.import_issuers([issuer_1, issuer_2, issuer_3])
# 2.5951875
utt_1 = ds.new_utterance('utt-1', file_1.idx, issuer_idx=issuer_1.idx)
utt_2 = ds.new_utterance('utt-2',
file_2.idx,
issuer_idx=issuer_2.idx,
start=0,
end=1.5)
utt_3 = ds.new_utterance('utt-3',
file_2.idx,
issuer_idx=issuer_2.idx,
start=1.5,
end=2.5)
# 5.0416875
utt_4 = ds.new_utterance('utt-4', file_3.idx, issuer_idx=issuer_3.idx)
utt_1.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who am i')]))
utt_2.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who are you')]))
utt_3.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who is he')]))
utt_4.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who are they')]))
train_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-1', 'utt-2', 'utt-3'})
sv_train = subview.Subview(ds, filter_criteria=[train_filter])
dev_filter = subview.MatchingUtteranceIdxFilter(utterance_idxs={'utt-4'})
sv_dev = subview.Subview(ds, filter_criteria=[dev_filter])
ds.import_subview('train', sv_train)
ds.import_subview('dev', sv_dev)
return ds
def _load(self, path):
corpus = audiomate.Corpus(path=path)
for part in SUBSETS:
sub_path = os.path.join(path, part)
ids = self.get_ids_from_folder(sub_path)
utt_ids = []
for idx in ids:
add_ids = self.load_file(sub_path, idx, corpus)
utt_ids.extend(add_ids)
subview_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs=utt_ids)
subview_corpus = subview.Subview(corpus,
filter_criteria=[subview_filter])
corpus.import_subview(part, subview_corpus)
TudaReader.create_wav_type_subviews(corpus,
utt_ids,
prefix='{}_'.format(part))
TudaReader.create_wav_type_subviews(corpus, corpus.utterances.keys())
return corpus
def test_match(self):
filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'a', 'b', 'd'})
self.assertTrue(filter.match(assets.Utterance('a', 'x'), None))
self.assertTrue(filter.match(assets.Utterance('b', 'x'), None))
self.assertTrue(filter.match(assets.Utterance('d', 'x'), None))
self.assertFalse(filter.match(assets.Utterance('c', 'x'), None))
self.assertFalse(filter.match(assets.Utterance('e', 'x'), None))
def test_match_inverse(self):
filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'a', 'b', 'd'}, inverse=True)
assert not filter.match(tracks.Utterance('a', 'x'), None)
assert not filter.match(tracks.Utterance('b', 'x'), None)
assert not filter.match(tracks.Utterance('d', 'x'), None)
assert filter.match(tracks.Utterance('c', 'x'), None)
assert filter.match(tracks.Utterance('e', 'x'), None)
def test_match(self):
utt_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'a', 'b', 'd'})
assert utt_filter.match(tracks.Utterance('a', 'x'), None)
assert utt_filter.match(tracks.Utterance('b', 'x'), None)
assert utt_filter.match(tracks.Utterance('d', 'x'), None)
assert not utt_filter.match(tracks.Utterance('c', 'x'), None)
assert not utt_filter.match(tracks.Utterance('e', 'x'), None)
def create_wav_type_subviews(corpus, utt_ids, prefix=''):
splits = collections.defaultdict(list)
for utt_id in utt_ids:
wavtype = utt_id.split('_')[-1]
splits[wavtype].append(utt_id)
for sub_name, sub_utts in splits.items():
subview_filter = subview.MatchingUtteranceIdxFilter(utterance_idxs=sub_utts)
subview_corpus = subview.Subview(corpus, filter_criteria=[subview_filter])
corpus.import_subview('{}{}'.format(prefix, sub_name), subview_corpus)
def test_import_subview(self):
train_set = subview.Subview(None,
filter_criteria=[
subview.MatchingUtteranceIdxFilter(
utterance_idxs={'existing_utt'})
])
self.corpus.import_subview('train', train_set)
assert self.corpus.num_subviews == 1
assert self.corpus.subviews['train'] == train_set
assert self.corpus.subviews['train'].corpus == self.corpus
def _subviews_from_utterance_splits(self, splits):
"""
Create subviews from a dict containing utterance-ids for each subview.
e.g. {'train': ['utt-1', 'utt-2'], 'test': [...], ...}
"""
subviews = {}
for idx, subview_utterances in splits.items():
filter = subview.MatchingUtteranceIdxFilter(utterance_idxs=subview_utterances)
split = subview.Subview(self.corpus, filter_criteria=filter)
subviews[idx] = split
return subviews
def _load(self, path):
corpus = audiomate.Corpus(path=path)
for part in SUBSETS:
sub_path = os.path.join(path, part)
ids = TudaReader.get_ids_from_folder(sub_path, part)
for idx in ids:
TudaReader.load_file(sub_path, idx, corpus)
subview_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs=ids)
subview_corpus = subview.Subview(corpus,
filter_criteria=[subview_filter])
corpus.import_subview(part, subview_corpus)
return corpus
def create_multi_label_corpus():
ds = audiomate.Corpus()
wav_1_path = sample_wav_file('wav_1.wav')
wav_2_path = sample_wav_file('wav_2.wav')
wav_3_path = sample_wav_file('wav_3.wav')
wav_4_path = sample_wav_file('wav_4.wav')
file_1 = ds.new_file(wav_1_path, track_idx='wav-1')
file_2 = ds.new_file(wav_2_path, track_idx='wav_2')
file_3 = ds.new_file(wav_3_path, track_idx='wav_3')
file_4 = ds.new_file(wav_4_path, track_idx='wav_4')
issuer_1 = ds.new_issuer('spk-1')
issuer_2 = ds.new_issuer('spk-2')
issuer_3 = ds.new_issuer('spk-3')
utt_1 = ds.new_utterance('utt-1', file_1.idx, issuer_idx=issuer_1.idx)
utt_2 = ds.new_utterance('utt-2', file_2.idx, issuer_idx=issuer_1.idx)
utt_3 = ds.new_utterance('utt-3',
file_3.idx,
issuer_idx=issuer_2.idx,
start=0,
end=15)
utt_4 = ds.new_utterance('utt-4',
file_3.idx,
issuer_idx=issuer_2.idx,
start=15,
end=25)
utt_5 = ds.new_utterance('utt-5',
file_3.idx,
issuer_idx=issuer_2.idx,
start=25,
end=40)
utt_6 = ds.new_utterance('utt-6',
file_4.idx,
issuer_idx=issuer_3.idx,
start=0,
end=15)
utt_7 = ds.new_utterance('utt-7',
file_4.idx,
issuer_idx=issuer_3.idx,
start=15,
end=25)
utt_8 = ds.new_utterance('utt-8',
file_4.idx,
issuer_idx=issuer_3.idx,
start=25,
end=40)
utt_1.set_label_list(
LabelList(labels=[
Label('music', 0, 5),
Label('speech', 5, 12),
Label('music', 13, 15)
]))
utt_2.set_label_list(
LabelList(labels=[
Label('music', 0, 5),
Label('speech', 5, 12),
Label('music', 13, 15)
]))
utt_3.set_label_list(
LabelList(labels=[Label('music', 0, 1),
Label('speech', 2, 6)]))
utt_4.set_label_list(
LabelList(labels=[
Label('music', 0, 5),
Label('speech', 5, 12),
Label('music', 13, 15)
]))
utt_5.set_label_list(LabelList(labels=[Label('speech', 0, 7)]))
utt_6.set_label_list(
LabelList(labels=[
Label('music', 0, 5),
Label('speech', 5, 12),
Label('music', 13, 15)
]))
utt_7.set_label_list(
LabelList(labels=[Label('music', 0, 5),
Label('speech', 5, 11)]))
utt_8.set_label_list(LabelList(labels=[Label('music', 0, 10)]))
train_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-4', 'utt-5', 'utt-6'})
sv_train = subview.Subview(ds, filter_criteria=[train_filter])
dev_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-7', 'utt-8'})
sv_dev = subview.Subview(ds, filter_criteria=[dev_filter])
ds.import_subview('train', sv_train)
ds.import_subview('dev', sv_dev)
ds.new_feature_container('mfcc', '/some/dummy/path/secondmfcc')
ds.new_feature_container('energy', '/some/dummy/path/energy')
return ds
def create_dataset():
temp_path = tempfile.mkdtemp()
ds = audiomate.Corpus(temp_path)
wav_1_path = sample_wav_file('wav_1.wav')
wav_2_path = sample_wav_file('wav_2.wav')
wav_3_path = sample_wav_file('wav_3.wav')
wav_4_path = sample_wav_file('wav_4.wav')
file_1 = ds.new_file(wav_1_path, track_idx='wav-1')
file_2 = ds.new_file(wav_2_path, track_idx='wav_2')
file_3 = ds.new_file(wav_3_path, track_idx='wav_3')
file_4 = ds.new_file(wav_4_path, track_idx='wav_4')
issuer_1 = Speaker('spk-1', gender=Gender.MALE)
issuer_2 = Speaker('spk-2', gender=Gender.FEMALE)
issuer_3 = Issuer('spk-3')
ds.import_issuers([issuer_1, issuer_2, issuer_3])
# duration 2.5951875
utt_1 = ds.new_utterance('utt-1', file_1.idx, issuer_idx=issuer_1.idx)
utt_2 = ds.new_utterance('utt-2', file_2.idx, issuer_idx=issuer_1.idx)
utt_3 = ds.new_utterance('utt-3',
file_3.idx,
issuer_idx=issuer_2.idx,
start=0,
end=1.5)
utt_4 = ds.new_utterance('utt-4',
file_3.idx,
issuer_idx=issuer_2.idx,
start=1.5,
end=2.5)
utt_5 = ds.new_utterance('utt-5', file_4.idx, issuer_idx=issuer_3.idx)
utt_1.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who am i')]))
utt_2.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who are you', meta={
'a': 'hey',
'b': 2
})]))
utt_3.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who is he')]))
utt_4.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who are they')]))
utt_5.set_label_list(
LabelList(audiomate.corpus.LL_WORD_TRANSCRIPT,
labels=[Label('who is she')]))
train_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-1', 'utt-2', 'utt-3'})
sv_train = subview.Subview(ds, filter_criteria=[train_filter])
dev_filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-4', 'utt-5'})
sv_dev = subview.Subview(ds, filter_criteria=[dev_filter])
ds.import_subview('train', sv_train)
ds.import_subview('dev', sv_dev)
ds.new_feature_container('mfcc', '/some/dummy/path')
ds.new_feature_container('mel', '/some/dummy/path_mel')
return ds
def test_serialize_inverse(self):
f = subview.MatchingUtteranceIdxFilter(utterance_idxs={'a', 'b', 'd'},
inverse=True)
assert f.serialize() == 'exclude,a,b,d'
def test_serialize(self):
f = subview.MatchingUtteranceIdxFilter(utterance_idxs={'a', 'b', 'd'})
assert f.serialize() == 'include,a,b,d'
def setUp(self):
filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-1', 'utt-3'})
self.corpus = resources.create_dataset()
self.subview = subview.Subview(self.corpus, filter_criteria=[filter])
def sample_subview():
filter = subview.MatchingUtteranceIdxFilter(
utterance_idxs={'utt-1', 'utt-3'})
corpus = resources.create_dataset()
return subview.Subview(corpus, filter_criteria=[filter])
