Learning Articulation from Cepstral Coefficients

Abstract

We work on a special case of the speech inversion problem, namely the mapping from Mel Frequency Cepstral Coeeficients onto articulatory trajectories, derived by EMA. We employ Support Vector Regression, and use PCA and ICA as means to account for the spatial structure of the problem. Our results are comparable to those achieved by older attempts on the same task, indicating probably some natural limitation on the mapping itself