COVAREP

A Cooperative Voice Analysis Repository for Speech Technologies [website].

Created with: John Kane (Trinity College Dublin, Dublin, Ireland), Thomas Drugman (University of Mons, Mons, Belgium), Tuomo Raitio (Aalto University, Espoo, Finland), Stefan Scherer (University of Southern California, Los Angeles, USA).

  • [PDF] 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.
    [Bibtex]
    @inproceedings{COVAREP2014,
    author = {G. Degottex and J. Kane and T. Drugman and T. Raitio and S. Scherer},
    booktitle = {Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
    title = {{COVAREP} - A collaborative voice analysis repository for speech technologies},
    address = {Florence, Italy},
    month = {May},
    year = {2014},
    abstract = {Speech processing algorithms are often developed demonstrating improvements over the state-of-the-art, but sometimes at the cost of high complexity. This makes algorithm reimplementations based on literature difficult, and thus reliable comparisons between published results and current work are hard to achieve. This paper presents a new collaborative and freely available repository for speech processing algorithms called COVAREP, which aims at fast and easy access to new speech processing algorithms and thus facilitating research in the field. We envisage that COVAREP allows more reproducible research by strengthening complex implementations through shared contributions and openly available code which can be discussed, commented on and corrected by the community. Presently COVAREP contains contributions from five distinct laboratories and we encourage contributions from across the speech processing research field. In this paper, we provide an overview of the current offerings of COVAREP and also include a demonstration of the algorithms through an emotion classification experiment.},
    url = {http://gillesdegottex.eu/wp-content/papercite-data/pdf/COVAREP2014.pdf},
    pdf = {http://gillesdegottex.eu/wp-content/papercite-data/pdf/COVAREP2014.pdf}
    }