def read_issuers(file_path, corpus):
if not os.path.isfile(file_path):
return
data = jsonfile.read_json_file(file_path)
for issuer_idx, issuer_data in data.items():
issuer_type = issuer_data.get('type', None)
issuer_info = issuer_data.get('info', {})
if issuer_type == 'speaker':
gender = issuers.Gender(
issuer_data.get('gender', 'unknown').lower())
age_group = issuers.AgeGroup(
issuer_data.get('age_group', 'unknown').lower())
native_language = issuer_data.get('native_language', None)
issuer = issuers.Speaker(issuer_idx,
gender=gender,
age_group=age_group,
native_language=native_language,
info=issuer_info)
elif issuer_type == 'artist':
name = issuer_data.get('name', None)
issuer = issuers.Artist(issuer_idx,
name=name,
info=issuer_info)
else:
issuer = issuers.Issuer(issuer_idx, info=issuer_info)
corpus.import_issuers(issuer)
def generate_issuers(n, rand=None):
if rand is None:
rand = random.Random()
items = []
for issuer_index in range(n):
issuer_idx = 'issuer-{}'.format(issuer_index)
issuer_type = rand.randint(1, 3)
if issuer_type == 1:
issuer = issuers.Speaker(
issuer_idx,
gender=issuers.Gender.UNKNOWN,
age_group=issuers.AgeGroup.CHILD,
native_language='de'
)
elif issuer_type == 2:
issuer = issuers.Artist(issuer_idx, 'badam')
else:
issuer = issuers.Issuer(issuer_idx)
items.append(issuer)
return items
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_import_utterance_no_issuer(self, corpus):
importing_utterances = [
tracks.Utterance('a', corpus.tracks['existing_file'],
issuers.Issuer('notexist'), 0, 10)
]
with pytest.raises(ValueError):
corpus.import_utterances(importing_utterances)
def test_import_issuers(self, corpus):
importing_issuers = [
issuers.Issuer('a'),
issuers.Issuer('b'),
issuers.Issuer('existing_issuer')
]
mapping = corpus.import_issuers(importing_issuers)
assert corpus.num_issuers == 4
assert 'a' in corpus.issuers.keys()
assert 'b' in corpus.issuers.keys()
assert 'existing_issuer_1' in corpus.issuers.keys()
assert len(mapping) == 3
assert mapping['a'].idx == 'a'
assert mapping['b'].idx == 'b'
assert mapping['existing_issuer'].idx == 'existing_issuer_1'
def corpus():
corpus = audiomate.Corpus()
ex_file = tracks.FileTrack('existing_file', '../any/path.wav')
ex_issuer = issuers.Issuer('existing_issuer')
ex_utterance = tracks.Utterance('existing_utt', ex_file, issuer=ex_issuer)
corpus.tracks['existing_file'] = ex_file
corpus.issuers['existing_issuer'] = ex_issuer
corpus.utterances['existing_utt'] = ex_utterance
return corpus
def setup_method(self):
self.ll_1 = annotations.LabelList(idx='alpha',
labels=[
annotations.Label('a', 3.2, 4.5),
annotations.Label('b', 5.1, 8.9),
annotations.Label(
'c', 7.2, 10.5),
annotations.Label('d', 10.5, 14),
annotations.Label('d', 15, 18)
])
self.ll_2 = annotations.LabelList(idx='bravo',
labels=[
annotations.Label('a', 1.0, 4.2),
annotations.Label('e', 4.2, 7.9),
annotations.Label(
'c', 7.2, 10.5),
annotations.Label('f', 10.5, 14),
annotations.Label('d', 15, 17.3)
])
self.ll_duplicate_idx = annotations.LabelList(
idx='charlie',
labels=[
annotations.Label('t', 1.0, 4.2),
annotations.Label('h', 4.2, 7.9)
])
self.ll_3 = annotations.LabelList(idx='charlie',
labels=[
annotations.Label('a', 1.0, 4.2),
annotations.Label('g', 4.2, 7.9)
])
self.track = tracks.FileTrack('wav',
resources.sample_wav_file('wav_1.wav'))
self.issuer = issuers.Issuer('toni')
self.utt = tracks.Utterance('test',
self.track,
issuer=self.issuer,
start=1.25,
end=1.30,
label_lists=[
self.ll_1, self.ll_2,
self.ll_duplicate_idx, self.ll_3
])
def new_issuer(self, issuer_idx, info=None):
"""
Add a new issuer to the dataset with the given data.
Parameters:
issuer_idx (str): The id to associate the issuer with. If None or already exists, one is
generated.
info (dict, list): Additional info of the issuer.
Returns:
Issuer: The newly added issuer.
"""
new_issuer_idx = issuer_idx
# Add index to idx if already existing
if new_issuer_idx in self._issuers.keys():
new_issuer_idx = naming.index_name_if_in_list(new_issuer_idx, self._issuers.keys())
new_issuer = issuers.Issuer(new_issuer_idx, info=info)
self._issuers[new_issuer_idx] = new_issuer
return new_issuer
def test_contains_issuer_returns_false(self, ds):
issuer = issuers.Issuer('spk-1')
res = ds.contains_issuer(issuer)
assert not res