def test_extract_features(utterances_index, features):
config = pipeline.get_default_config(features,
with_cmvn=False,
with_pitch=False)
feats = pipeline.extract_features(config, utterances_index)
feat1 = feats[utterances_index[0][0]]
assert feat1.is_valid()
assert feat1.shape[0] == 140
assert feat1.dtype == np.float32
config = pipeline.get_default_config(features,
with_cmvn=False,
with_pitch=True)
feats = pipeline.extract_features(config, utterances_index)
feat2 = feats[utterances_index[0][0]]
assert feat2.is_valid()
assert feat2.shape[0] == 140
assert feat2.shape[1] == feat1.shape[1] + 3
utterances_index = [('u1', utterances_index[0][1], 0, 1)]
config = pipeline.get_default_config(features,
with_cmvn=False,
with_pitch=False)
feats = pipeline.extract_features(config, utterances_index)
feat3 = feats[utterances_index[0][0]]
assert feat3.is_valid()
assert feat3.shape[0] == 98
assert feat3.shape[1] == feat1.shape[1]
def test_config_good(features):
c1 = pipeline.get_default_config(features, to_yaml=False)
c2 = pipeline.get_default_config(
features, to_yaml=True, yaml_commented=False)
c3 = pipeline.get_default_config(
features, to_yaml=True, yaml_commented=True)
assert features in c1.keys()
assert '#' not in c2
assert '#' in c3
assert equal_dict(c1, yaml.load(c2, Loader=yaml.FullLoader))
assert equal_dict(c1, yaml.load(c3, Loader=yaml.FullLoader))
def command_config(args):
config = pipeline.get_default_config(
args.features,
to_yaml=True, yaml_commented=not args.no_comments,
with_pitch=not args.no_pitch,
with_cmvn=not args.no_cmvn,
with_delta=not args.no_delta)
output = sys.stdout if not args.output else open(args.output, 'w')
output.write(config)
def test_cmvn(utterances_index, by_speaker, with_vad):
config = pipeline.get_default_config(
'mfcc', with_cmvn=True, with_pitch=False, with_delta=False)
config['cmvn']['by_speaker'] = by_speaker
config['cmvn']['with_vad'] = with_vad
feats = pipeline.extract_features(config, utterances_index)
feat2 = feats[utterances_index[0][0]]
assert feat2.is_valid()
assert feat2.shape[0] == 140
assert feat2.shape[1] == 13
def test_check_speakers(utterances_index, capsys):
log = utils.get_logger(level='info')
config = pipeline.get_default_config('mfcc')
with pytest.raises(ValueError) as err:
pipeline.extract_features(config, [(utterances_index[0][1], )],
log=log)
assert 'no speaker information provided' in str(err)
capsys.readouterr() # clean the buffer
config = pipeline.get_default_config('mfcc', with_cmvn=False)
pipeline.extract_features(config, utterances_index, log=log)
log_out = capsys.readouterr()
assert 'cmvn' not in log_out.err
assert '(CMVN disabled)' in log_out.err
config = pipeline.get_default_config('mfcc', with_cmvn=True)
config['cmvn']['by_speaker'] = False
pipeline.extract_features(config, utterances_index, log=log)
log_out = capsys.readouterr().err
assert 'cmvn by utterance' in log_out
assert '(CMVN by speaker disabled)' in log_out
def generate_configurations(conf_directory):
try:
os.makedirs(conf_directory)
except FileExistsError:
pass
for features in pipeline.valid_features():
conf = os.path.join(conf_directory, f'{features}_only.yaml')
yaml = pipeline.get_default_config(
features, to_yaml=True, yaml_commented=False,
with_cmvn=False, with_delta=False, with_pitch=False)
open(conf, 'w').write(yaml)
conf = os.path.join(conf_directory, f'{features}_nocmvn.yaml')
yaml = pipeline.get_default_config(
features, to_yaml=True, yaml_commented=False,
with_cmvn=False, with_delta=True, with_pitch=True)
open(conf, 'w').write(yaml)
conf = os.path.join(conf_directory, f'{features}_full.yaml')
yaml = pipeline.get_default_config(
features, to_yaml=True, yaml_commented=False,
with_cmvn=True, with_delta=True, with_pitch=True)
open(conf, 'w').write(yaml)
def test_config_format(utterances_index, capsys, tmpdir, kind):
config = pipeline.get_default_config('mfcc', to_yaml=kind != 'dict')
if kind == 'file':
tempfile = str(tmpdir.join('foo'))
open(tempfile, 'w').write(config)
config = tempfile
if kind == 'str':
config2 = 'a:\nb\n'
with pytest.raises(ValueError) as err:
pipeline._init_config(config2)
assert 'error in configuration' in str(err)
parsed = pipeline._init_config(config, log=utils.get_logger(level='info'))
output = capsys.readouterr().err
for word in ('mfcc', 'pitch', 'cmvn', 'delta'):
assert word in output
assert word in parsed
def test_config_bad(utterances_index):
with pytest.raises(ValueError) as err:
pipeline.get_default_config('bad')
assert 'invalid features "bad"' in str(err)
config = pipeline.get_default_config('mfcc')
del config['mfcc']
with pytest.raises(ValueError) as err:
pipeline.extract_features(config, utterances_index)
assert 'the configuration does not define any features' in str(err)
config = pipeline.get_default_config('mfcc')
config['plp'] = config['mfcc']
with pytest.raises(ValueError) as err:
pipeline.extract_features(config, utterances_index)
assert 'more than one features extraction processor' in str(err)
config = pipeline.get_default_config('mfcc')
config['invalid'] = config['mfcc']
with pytest.raises(ValueError) as err:
pipeline.extract_features(config, utterances_index)
assert 'invalid keys in configuration' in str(err)
config = pipeline.get_default_config('mfcc')
del config['cmvn']['with_vad']
parsed = pipeline._init_config(config)
assert 'cmvn' in parsed
assert parsed['cmvn']['with_vad']
config = pipeline.get_default_config('mfcc')
del config['cmvn']['by_speaker']
c = pipeline._init_config(config)
assert not c['cmvn']['by_speaker']
config = pipeline.get_default_config('mfcc')
del config['pitch']['postprocessing']
c = pipeline._init_config(config)
assert c['pitch']['postprocessing'] == {}
def test_extract_features_full(ext, wav_file, wav_file_8k, wav_file_float32,
capsys, tmpdir):
# difficult case with parallel jobs, different sampling rates,
# speakers and segments
index = [('u1', wav_file, 's1', 0, 1),
('u2', wav_file_float32, 's2', 1, 1.2),
('u3', wav_file_8k, 's1', 1, 3)]
config = pipeline.get_default_config('mfcc')
# disable VAD because it can alter the cmvn result (far from (0,
# 1) when the signal includes non-voiced frames)
config['cmvn']['with_vad'] = False
feats = pipeline.extract_features(config,
index,
njobs=2,
log=utils.get_logger())
# ensure we have the expected log messages
messages = capsys.readouterr().err
assert 'INFO - get 3 utterances from 2 speakers in 3 wavs' in messages
assert 'WARNING - several sample rates found in wav files' in messages
for utt in ('u1', 'u2', 'u3'):
assert utt in feats
assert feats[utt].dtype == np.float32
# check properies
p1 = feats['u1'].properties
p2 = feats['u2'].properties
p3 = feats['u3'].properties
assert p1['audio']['file'] == wav_file
assert p1['audio']['duration'] == 1.0
assert p2['audio']['file'] == wav_file_float32
assert p2['audio']['duration'] == pytest.approx(0.2)
assert p3['audio']['file'] == wav_file_8k
assert p3['audio']['duration'] < 0.5 # ask 3s but get duration-tstart
assert p1['mfcc'] == p2['mfcc']
assert p1['mfcc']['sample_rate'] != p3['mfcc']['sample_rate']
assert p1.keys() == {
'audio', 'mfcc', 'cmvn', 'pitch', 'delta', 'speaker', 'pipeline'
}
assert p1.keys() == p2.keys() == p3.keys()
assert p1['pipeline'] == p2['pipeline'] == p3['pipeline']
# check shape. mfcc*delta + pitch = 13 * 3 + 3 = 42
assert feats['u1'].shape == (98, 42)
assert feats['u2'].shape == (18, 42)
assert feats['u3'].shape == (40, 42)
# check cmvn
assert feats['u2'].data[:, :13].mean() == pytest.approx(0.0, abs=1e-6)
assert feats['u2'].data[:, :13].std() == pytest.approx(1.0, abs=1e-6)
data = np.vstack((feats['u1'].data[:, :13], feats['u3'].data[:, :13]))
assert data.mean() == pytest.approx(0.0, abs=1e-6)
assert data.std() == pytest.approx(1.0, abs=1e-6)
assert np.abs(data.mean()) <= np.abs(feats['u1'].data[:, :13].mean())
assert np.abs(data.std() - 1.0) <= np.abs(feats['u1'].data[:, :13].std() -
1.0)
assert np.abs(data.mean()) <= np.abs(feats['u3'].data[:, :13].mean())
assert np.abs(data.std() - 1.0) <= np.abs(feats['u3'].data[:, :13].std() -
1.0)
# save / load the features
filename = str(tmpdir.join('feats' + ext))
feats.save(filename)
feats2 = FeaturesCollection.load(filename)
assert feats2 == feats
def fun(utts):
c = pipeline._init_config(
pipeline.get_default_config('mfcc', with_cmvn=False))
u = pipeline._init_utterances(utts)
pipeline._Manager(c, u)
return u
