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@INPROCEEDINGS{Lazaridis_ODYSSEY_2014,
         author = {Lazaridis, Alexandros and Khoury, Elie and Goldman, Jean-Philippe and Avanzi, Mathieu and Marcel, S{\'{e}}bastien and Garner, Philip N.},
       keywords = {Accent Identification, French Regional Accents, GMM Modelling, i-vectors, SVM},
       projects = {Idiap, SIWIS, SNSF-LOBI},
          title = {SWISS FRENCH REGIONAL ACCENT IDENTIFICATION},
      booktitle = {Odyssey: The Speaker and Language Recognition Workshop},
           year = {2014},
       abstract = {In this paper an attempt is made to automatically recognize the speaker’s accent among regional Swiss French accents from four different regions of Switzerland, i.e. Geneva (GE), Martigny (MA), Neuchˆatel (NE) and Nyon (NY). To achieve this goal, we rely on a generative probabilistic framework for classification based on Gaussian mixture modelling (GMM). Two different GMM-based algorithms are investigated: (1) the baseline technique of universal background modelling (UBM) followed by maximum-a-posteriori (MAP) adaptation, and (2) total variability (i-vector) modelling. Both systems perform well, with the i-vector-based system outperforming the baseline system, achieving a relative improvement of 17.1\% in the overall regional accent identification accuracy.},
            pdf = {https://publications.idiap.ch/attachments/papers/2014/Lazaridis_ODYSSEY_2014.pdf}
}