__init__.py 5.13 KB
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# -*- coding: utf-8 -*-
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#
# This file is part of SIDEKIT.
#
# SIDEKIT is a python package for speaker verification.
# Home page: http://www-lium.univ-lemans.fr/sidekit/
#
# SIDEKIT is a python package for speaker verification.
# Home page: http://www-lium.univ-lemans.fr/sidekit/
#    
# SIDEKIT is free software: you can redistribute it and/or modify
# it under the terms of the GNU LLesser General Public License as 
# published by the Free Software Foundation, either version 3 of the License, 
# or (at your option) any later version.
#
# SIDEKIT is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with SIDEKIT.  If not, see <http://www.gnu.org/licenses/>.
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"""
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Copyright 2014-2016 Anthony Larcher and Sylvain Meignier
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:mod:`frontend` provides methods to process an audio signal in order to extract
useful parameters for speaker verification.
"""
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import logging
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import numpy
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import os
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import sys
from ctypes import *
from ctypes.util import find_library
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PARALLEL_MODULE = 'multiprocessing'  # can be , threading, multiprocessing MPI is planned in the future
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PARAM_TYPE = numpy.float32
STAT_TYPE = numpy.float64
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THEANO_CONFIG = "gpu"  # can be gpu or cpu
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# Import bosaris-like classes
from sidekit.bosaris import IdMap
from sidekit.bosaris import Ndx
from sidekit.bosaris import Key
from sidekit.bosaris import Scores
from sidekit.bosaris import DetPlot
from sidekit.bosaris import effective_prior
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from sidekit.bosaris import logit_effective_prior
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from sidekit.bosaris import fast_minDCF

# Import classes
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from sidekit.features_extractor import FeaturesExtractor
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from sidekit.features_server import FeaturesServer
from sidekit.mixture import Mixture
from sidekit.statserver import StatServer

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from sidekit.frontend.io import write_pcm
from sidekit.frontend.io import read_pcm
from sidekit.frontend.io import pcmu2lin
from sidekit.frontend.io import read_sph
from sidekit.frontend.io import write_label
from sidekit.frontend.io import read_label
from sidekit.frontend.io import read_spro4
from sidekit.frontend.io import read_audio
from sidekit.frontend.io import write_spro4
from sidekit.frontend.io import read_htk
from sidekit.frontend.io import write_htk

from sidekit.frontend.vad import vad_energy
from sidekit.frontend.vad import vad_snr
from sidekit.frontend.vad import label_fusion
from sidekit.frontend.vad import speech_enhancement


from sidekit.frontend.normfeat import cms
from sidekit.frontend.normfeat import cmvn
from sidekit.frontend.normfeat import stg
from sidekit.frontend.normfeat import rasta_filt


from sidekit.frontend.features import compute_delta
from sidekit.frontend.features import framing
from sidekit.frontend.features import pre_emphasis
from sidekit.frontend.features import trfbank
from sidekit.frontend.features import mel_filter_bank
from sidekit.frontend.features import mfcc
from sidekit.frontend.features import pca_dct
from sidekit.frontend.features import shifted_delta_cepstral

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from sidekit.iv_scoring import cosine_scoring
from sidekit.iv_scoring import mahalanobis_scoring
from sidekit.iv_scoring import two_covariance_scoring
from sidekit.iv_scoring import PLDA_scoring

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from sidekit.gmm_scoring import gmm_scoring 

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from sidekit.jfa_scoring import jfa_scoring

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# Import NNET classes and functions
try:
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    if THEANO_CONFIG == "gpu":
        os.environ['THEANO_FLAGS'] = 'mode=FAST_RUN,device=gpu,floatX=float32'
    else:
        os.environ['THEANO_FLAGS'] = 'mode=FAST_RUN,device=cpu,floatX=float32'

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    import theano
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    from sidekit.nnet.feed_forward import FForwardNetwork
    print("Import theano")
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except ImportError:
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    print("Cannot import Theano")
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from sidekit.sv_utils import clean_stat_server
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libsvm_loaded = False
try:
    dirname = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'libsvm')
    if sys.platform == 'win32':
        libsvm = CDLL(os.path.join(dirname, r'libsvm.dll'))
        libsvm_loaded = True
    else:
        libsvm = CDLL(os.path.join(dirname, 'libsvm.so.2'))
        libsvm_loaded = True
except:
    # For unix the prefix 'lib' is not considered.
    if find_library('svm'):
        libsvm = CDLL(find_library('svm'))
        libsvm_loaded = True
    elif find_library('libsvm'):
        libsvm = CDLL(find_library('libsvm'))
        libsvm_loaded = True
    else:
        libsvm_loaded = False
        logging.warning('WARNNG: libsvm is not installed, please refer to the' +
                        ' documentation if you intend to use SVM classifiers')

if libsvm_loaded:
    from sidekit.libsvm import *
    from sidekit.svm_scoring import *
    from sidekit.svm_training import *

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__author__ = "Anthony Larcher and Sylvain Meignier"
__copyright__ = "Copyright 2014-2016 Anthony Larcher and Sylvain Meignier"
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__license__ = "LGPL"
__maintainer__ = "Anthony Larcher"
__email__ = "anthony.larcher@univ-lemans.fr"
__status__ = "Production"
__docformat__ = 'reStructuredText'

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# __all__ = ["io",
#            "vad",
#            "normfeat",
#            "features"
#            ]