Metadata-Version: 1.1
Name: xspear.fast-plda
Version: 1.0.0
Summary: Speaker recognition toolchain for NIST SRE 2012
Home-page: http://pypi.python.org/pypi/spear.fast_plda
Author: Elie Khoury
Author-email: Elie.Khoury@idiap.ch
License: GPLv3
Description: Toolchain for fast and scalable PLDA
        ====================================
        
        This package contains scripts that run the fast and scalable PLDA that was introduced in [1]. The package uses the framework of Bob `Spear` for handling the protocol, the toolchain and doing the post-processing (whitening and length-normalization). 
        
        If you use this package and/or its results, please you must cite the following publications:
        
        [1] The original Fast PLDA paper published at S+SSPR 2014::
        
            @inproceedings{Sizov,
              author = {Sizov, A and Lee, K.A. and Kinnunen, T.},
              title = {Unifying Probabilistic Linear Discriminant Analysis Variants in Biometric Authentication},
              booktitle = {Proc. S+SSPR},
              year = {2014},
              url = {to appear},
            }
        
        
        [2] The Spear paper published at ICASSP 2014::
        
            @inproceedings{spear,
              author = {Khoury, E. and El Shafey, L. and Marcel, S.},
              title = {Spear: An open source toolbox for speaker recognition based on {B}ob},
              booktitle = {IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)},
              year = {2014},
              url = {http://publications.idiap.ch/downloads/papers/2014/Khoury_ICASSP_2014.pdf},
            }
        
        
        Installation
        ------------
        
        Just download this package and decompress it locally::
        
          $ wget http://pypi.python.org/packages/source/x/xspear.fast_plda/xspear.fast_plda-1.0.0.zip
          $ unzip xspear.fast_plda-1.0.0.zip
          $ cd xspear.fast_plda-1.0.0.zip
        
        Use buildout to bootstrap and have a working environment ready for
        experiments::
        
          $ python bootstrap
          $ ./bin/buildout
        
        This also requires that bob (>= 1.2.0) is installed.
        
        
        Example of use
        --------------
        
        The following command is intended to run the entire experiment for a protocol defined in "protocol.py"::
        
          $  bin/ivec_whitening_lnorm.py -d protocol.py -t config/fast_plda.py -T PATH/TO/TEMP_DIR -U PATH/TO/RESULTS_DIR 
          
        For more details and options, please type::
        
          $ bin/ivec_whitening_lnorm.py --help  
        
        .. _Spear: https://pypi.python.org/pypi/bob.spear/
        
Keywords: bob,xbob,xbob.db,speaker recognition
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
