• DocumentCode
    177758
  • Title

    COVAREP — A collaborative voice analysis repository for speech technologies

  • Author

    Degottex, Gilles ; Kane, John ; Drugman, Thomas ; Raitio, Tuomo ; Scherer, Stefan

  • Author_Institution
    Comput. Sci. Dept., Univ. of Crete, Heraklion, Greece
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    960
  • Lastpage
    964
  • 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 will allow 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.
  • Keywords
    speech processing; COVAREP; collaborative voice analysis repository; complexity cost; emotion classification experiment; speech processing algorithm; speech processing research field; speech technology; Adaptation models; Estimation; Feature extraction; Harmonic analysis; Signal processing algorithms; Speech; Speech processing; Speech processing; glottal source; sinusoidal modeling; spectral envelope; toolkit; voice quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6853739
  • Filename
    6853739