Total: 1
In this paper, we present our efforts towards deriving vocal tract shapes from ElectroMagnetic Articulograph data (EMA) via geometric adaptation and matching. We describe a novel approach for adapting Maedas geometric model of the vocal tract to one speaker in the MOCHA database. We show how we can rely solely on the EMA data for adaptation. We present our search technique for the vocal tract shapes that best fit the given EMA data. We then describe our approach of synthesizing speech from these shapes. Results on Mel-cepstral distortion reflect improvement in synthesis over the approach we used before without adaptation.