def __init__(self, conf, segment_lengths):
"""Matrix2MatrixProcessor constructor
Args:
conf: Matrix2MatrixProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# the number of rows in the matrix
self.nrCol = int(conf['nrcol'])
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# set the type of mean and variance normalisation
self.mvn_type = conf['mvn_type']
if conf['mvn_type'] == 'global':
self.obs_cnt = 0
self.glob_mean = np.zeros([self.nrCol])
self.glob_std = np.zeros([self.nrCol])
elif conf['mvn_type'] == 'None':
pass
else:
raise Exception('Unknown way to apply mvn: %s' % conf['mvn_type'])
super(Matrix2MatrixProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""AudioFeatProcessor constructor
Args:
conf: AudioFeatProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.dim = self.comp.get_dim()
self.max_length = np.zeros(len(self.segment_lengths))
# self.sequence_length_histogram = np.zeros(0, dtype=np.int32)
self.nontime_dims = [self.dim]
# set the type of mean and variance normalisation
self.mvn_type = conf['mvn_type']
if conf['mvn_type'] == 'global':
self.obs_cnt = 0
self.glob_mean = np.zeros([1, self.dim])
self.glob_std = np.zeros([1, self.dim])
elif conf['mvn_type'] in ['local', 'none', 'None', 'from_files']:
pass
else:
raise Exception('Unknown way to apply mvn: %s' % conf['mvn_type'])
super(AudioFeatProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""MultiTargetProcessor constructor
Args:
conf: MultiTargetProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
self.dim = self.comp.get_dim()
# initialize the metadata
self.nrS = int(conf['nrs'])
self.target_dim = self.comp.get_dim()
self.nontime_dims = [self.target_dim, self.nrS]
if 'mvn_type' in conf:
self.mvn_type = conf['mvn_type']
else:
self.mvn_type = 'None'
if self.mvn_type == 'global':
self.obs_cnt = 0
self.glob_mean = np.zeros([1, self.dim])
self.glob_std = np.zeros([1, self.dim])
elif self.mvn_type in ['local', 'none', 'None', 'from_files']:
pass
else:
raise Exception('Unknown way to apply mvn: %s' % conf['mvn_type'])
super(MultiTargetProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""IdealRatioProcessor constructor
Args:
conf: IdealRatioProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
if 'pow' not in conf['feature']:
raise Exception('expecting feature to be in power domain')
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
if 'apply_sqrt' in conf and conf['apply_sqrt'] != 'True':
self.apply_sqrt = False
else:
self.apply_sqrt = True
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.nr_channels = int(conf['nr_channels'])
self.dim = self.comp.get_dim()
self.nontime_dims = [self.dim]
super(IdealRatioMultimicProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""VadTimingsProcessor constructor
Args:
conf: VadTimingsProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory('frames')(conf)
self.winlen = float(conf['winlen'])
self.winstep = float(conf['winstep'])
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
self.nrS = int(conf['nrs'])
# initialize the metadata
self.dim = self.nrS
self.max_length = np.zeros(len(self.segment_lengths))
# self.sequence_length_histogram = np.zeros(0, dtype=np.int32)
self.nontime_dims = [self.dim]
super(VadTimingsProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""onehotperfeatureTargetProcessor constructor
Args:
conf: onehotperfeatureTargetProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.nrS = int(conf['nrs'])
if 'spk_select' in conf:
self.nrS_select = map(int, conf['spk_select'].split(' '))
else:
self.nrS_select = range(0, self.nrS)
self.nr_channels = int(conf['nr_channels'])
self.dim = self.comp.get_dim() * len(self.nrS_select)
self.nontime_dims = [self.dim]
super(onehotperfeatureTargetMultimicProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""AudioFeatProcessor constructor
Args:
conf: SpatialFeatProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# the channel pairs for which to compute the spatial features
channel_pairs = conf['channels_pairs'].split(' ')
channel_pairs = [map(int, pair.split('-')) for pair in channel_pairs]
self.channel_pairs = [[ch - 1 for ch in pair] for pair in channel_pairs
] # python index starts at 0
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.dim = self.comp.get_dim() * 2 * len(channel_pairs)
self.max_length = np.zeros(len(self.segment_lengths))
# self.sequence_length_histogram = np.zeros(0, dtype=np.int32)
self.nontime_dims = [self.dim]
super(SpatialFeatProcessor, self).__init__(conf)
def __init__(self,
conf,
proc_conf,
evalconf,
expdir,
rec_dir,
task,
name=None):
'''IvectorExtractor constructor
Args:
conf: the ivector_extractor configuration as a dictionary
proc_conf: the processor configuration for the postprocessor, as a dict
evalconf: the evaluator configuration as a ConfigParser
expdir: the experiment directory
rec_dir: the directory where the reconstructions are
task: name of the task
'''
super(IvectorExtractor, self).__init__(conf, proc_conf, evalconf,
expdir, rec_dir, task, name)
#The directory where all models for iVector extraction are stored. E.g. the
#Universal Background Model (UBM), the total variability matrix, ...
self.model_dir = conf['model_dir']
UBM_w_file = os.path.join(self.model_dir, 'UBM_w.npy')
self.UBM_w = np.load(UBM_w_file)
UBM_mu_file = os.path.join(self.model_dir, 'UBM_mu.npy')
self.UBM_mu = np.load(UBM_mu_file)
UBM_sigma_file = os.path.join(self.model_dir, 'UBM_sigma.npy')
self.UBM_sigma = np.load(UBM_sigma_file)
TV_file = os.path.join(self.model_dir,
'T%d.npy' % (int(conf['tv_dim'])))
self.TV = np.load(TV_file)
self.apply_lda = conf['lda'] == 'True'
if self.apply_lda:
V_file = os.path.join(self.model_dir, 'V.npy')
self.V = np.load(V_file)
self.V = self.V[:int(conf['v_dim']), :]
#create the feature computer
self.comp = feature_computer_factory.factory(
proc_conf['feature'])(proc_conf)
self.VAD_thres = float(proc_conf['vad_thres'])
def __init__(self, conf):
'''AudioProcessor constructor
Args:
conf: processor configuration as a configparser
'''
#create the feature computer
self.comp = feature_computer_factory.factory(
conf.get('feature', 'feature'))(conf)
#initialize the metadata
self.dim = self.comp.get_dim()
self.max_length = 0
self.sequence_length_histogram = np.zeros(0, dtype=np.int32)
super(AudioProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""AudioMultiSignalProcessor constructor
Args:
conf: AudioMultiSignalProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.dim = self.comp.get_dim()
super(AudioMultiSignalProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""indexProcessor constructor
Args:
conf: indexProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# create the string label to index dictionary
self.nrS = int(conf['nrs'])
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
super(indexProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
'''Strlabel2indexProcessor constructor
Args:
conf: Strlabel2indexProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths'''
#create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
#create the string label to index dictionary
self.label2index = dict()
self.next_index = 0
#set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
super(Strlabel2indexProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
'''IdealRatioProcessor constructor
Args:
conf: IdealRatioProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths'''
#create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
#set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
#initialize the metadata
self.dim = self.comp.get_dim()
self.nontime_dims = [self.dim]
super(IdealRatioProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""onehotperfeatureTargetProcessor constructor
Args:
conf: onehotperfeatureTargetProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.nrS = int(conf['nrs'])
self.dim = self.comp.get_dim() * self.nrS
self.nontime_dims = [self.dim]
super(onehotperfeatureTargetProcessor, self).__init__(conf)
def __init__(self, conf, segment_lengths):
"""ScorelabelperfeatureProcessor constructor
Args:
conf: ScorelabelperfeatureProcessor configuration as a dict of strings
segment_lengths: A list containing the desired lengths of segments.
Possibly multiple segment lengths"""
# create the feature computer
self.comp = feature_computer_factory.factory(conf['feature'])(conf)
self.mag_thres = float(conf['mag_thres'])
# set the length of the segments. Possibly multiple segment lengths
self.segment_lengths = segment_lengths
# initialize the metadata
self.dim = self.comp.get_dim()
self.nontime_dims = [self.dim]
super(ScorelabelperfeatureProcessor, self).__init__(conf)
