A Cooperative Voice Analysis Repository for Speech Technologies
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        A Cooperative Voice Analysis Repository for Speech Technologies
                            Version (after 1.4.1)

Covarep is an open-source repository of advanced speech processing algorithms
and is stored as a GitHub project (https://github.com/covarep/covarep) where
researchers in speech processing can store original implementations of published

Over the past few decades a vast array of advanced speech processing algorithms
have been developed, often offering significant improvements over the existing
state-of-the-art. Such algorithms can have a reasonably high degree of
complexity and, hence, can be difficult to accurately re-implement based on
article descriptions. Another issue is the so-called 'bug magnet effect' with
re-implementations frequently having significant differences from the original
ones. The consequence of all this has been that many promising developments
have been under-exploited or discarded, with researchers tending to stick to
conventional analysis methods.

By developing Covarep we are hoping to address this by encouraging authors to
include original implementations of their algorithms, thus resulting in a
single de facto version for the speech community to refer to.

We envisage a range of benefits to the repository:

1) Reproducible research: Covarep will allow fairer comparison of algorithms
in published articles.

2) Encouraged usage: the free availability of these algorithms will encourage
researchers from a wide range of speech-related disciplines to exploit them
for their own applications.

3) Feedback: as a GitHub project users will be able to offer comments on
algorithms, report bugs, suggest improvements etc.

    We welcome contributions from a wide range of speech processing areas,
    including (but not limited to): Speech analysis, synthesis, conversion,
    transformation, enhancement, glottal source/voice quality analysis, etc.

    We believe that the Covarep repository has a great potential benefit to the
    speech research community and we hope that you will consider contributing
    your published algorithms to it. If you have any questions, comments issues
    etc regarding Covarep please contact us on one of the email addresses below.
    Please forward this email to others who may be interested.

Please also have a look at the webiste http://covarep.github.io/covarep and the
Covarep.pdf document in the documentation directory for more information.

    Most of the functions in Covarep are Octave compatible.
    However, it is necessary to install the following packages:
        tsa, optimization, signal.

How to cite
    If you publish experiment results obtained by using Covarep, please cite
    the repository using the following publication:
      G. Degottex, J. Kane, T. Drugman, T. Raitio and S. Scherer, "COVAREP - A
      collaborative voice analysis repository for speech technologies", In
      Proc. IEEE International Conference on Acoustics, Speech and Signal
      Processing (ICASSP), Florence, Italy 2014.

    Also, within the text of your paper, please mention the version used.
    E.g. "... we compared with methods X, Y, Z available in [Covarep](v1.0.1)."

    Gilles Degottex <degottex@csd.uoc.gr>
        University of Crete, Heraklion, Greece

    John Kane <kanejo@tcd.ie>
        Trinity College Dublin, Dublin, Ireland
    Thomas Drugman <thomas.drugman@umons.ac.be>
        University of Mons, Mons, Belgium
    Tuomo Raitio <tuomo.raitio@aalto.fi>
        Aalto University, Espoo, Finland

    Stefan Scherer <scherer@ict.usc.edu>
        University of Southern California, Los Angeles, USA