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        "author": "Elie Khoury",
        "author_email": "Elie.Khoury@idiap.ch",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Education",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Natural Language :: English",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Topic :: Database :: Front-Ends",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "Speaker recognition protocol on the Voxforge Database \n=====================================================\n\n`Voxforge`_ offers a collection transcribed speech for use with **Free** and **Open Source Speech Recognition Engines**. \nIn this package, we design a speaker recognition protocol that uses a **small subset of the english audio files** (only 6561 files) belonging to **30 speakers** randomly selected.\nThis subset is split into three equivalent parts: Training (10 speakers), Development (10 speakers) and Test (10 speakers) sets.\n \nThis package serves as a toy example of speaker recognition database while testing `xbob.spkrec`_.\n\nThe `xbob.spkrec`_  is developed at Idiap during its participation to the `NIST SRE 2012 evaluation`_. If you use this package and/or its results, please cite the following\npublications:\n\n1. The original paper presented at the NIST SRE 2012 workshop::\n\n     @inproceedings{Khoury_NISTSRE_2012,\n       author = {Khoury, Elie and El Shafey, Laurent and Marcel, S{\\'{e}}bastien},\n       month = {dec},\n       title = {The Idiap Speaker Recognition Evaluation System at NIST SRE 2012},\n       booktitle = {NIST Speaker Recognition Conference},\n       year = {2012},\n       location = {Orlando, USA},\n       organization = {NIST},\n       pdf = {http://publications.idiap.ch/downloads/papers/2012/Khoury_NISTSRE_2012.pdf}\n    }\n\n2. Bob as the core framework used to run the experiments::\n\n    @inproceedings{Anjos_ACMMM_2012,\n      author = {A. Anjos and L. El Shafey and R. Wallace and M. G\\\"unther and C. McCool and S. Marcel},\n      title = {Bob: a free signal processing and machine learning toolbox for researchers},\n      year = {2012},\n      month = oct,\n      booktitle = {20th ACM Conference on Multimedia Systems (ACMMM), Nara, Japan},\n      publisher = {ACM Press},\n      url = {http://publications.idiap.ch/downloads/papers/2012/Anjos_Bob_ACMMM12.pdf},\n    }\n\n\n\nInstallation\n------------\n\nJust download this package and decompress it locally::\n\n  $ wget http://pypi.python.org/packages/source/x/xbob.db.voxforge/xbob.db.voxforge-0.0.1a2.zip\n  $ unzip xbob.db.voxforge-0.0.1a2.zip\n  $ cd xbob.db.voxforge-0.0.1a2\n\nUse buildout to bootstrap and have a working environment ready for\nexperiments::\n\n  $ python bootstrap\n  $ ./bin/buildout\n\nThis also requires that bob (>= 1.2.0) is installed.\n\n\nGetting the data\n~~~~~~~~~~~~~~~~\n\nThe data can be downloaded from its original URL (on Voxforge) and extracted by running `download_and_untar.sh`_ that takes as input the path in which the data will be stored::\n\n  $ ./download_and_untar.sh PATH/TO/WAV/DIRECTORY\n\n.. _Voxforge: http://www.voxforge.org/\n.. _xbob.spkrec: https://github.com/bioidiap/xbob.spkrec\n.. _NIST SRE 2012 evaluation: http://www.nist.gov/itl/iad/mig/sre12.cfm\n.. _download_and_untar.sh: https://github.com/bioidiap/xbob.db.voxforge/blob/master/download_and_untar.sh\n\nIn case you need a help, please contact us.",
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        "keywords": "Speaker Recognition,Speaker verification,Gaussian Mixture Model,ISV,UBM-GMM,I-Vector,Audio processing,Database,Voxforge",
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