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Publication
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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.
Annalisa Buffa, Jochen Peter Hinz, Ondine Gabrielle Chanon, Alessandra Arrigoni
Pablo Antolin Sanchez, Ondine Gabrielle Chanon
Annalisa Buffa, Rafael Vazquez Hernandez, Ondine Gabrielle Chanon