Mapping the Speech Signal onto Electromagnetic Articulography Trajectories Using Support Vector Regression

Abstract. We report work on the mapping between the speech signal and articulatory trajectories from the MOCHA database. Contrasting previous works that used Neural Networks for the same task, we employ Support Vector Regression as our main tool, and Principal Component Analysis as an auxiliary one. Our results are comparable, even though, due to training time considerations we use only a small portion of the available data.

• Type: Conference
• Year: 2005
• Where: TSD
• Authors: Asterios Toutios, Konstantinos G. Margaritis
• Keywords: Articulatory Trajectories, Principal Component Analysis, Signal Processing, Support Vector Regression, TSD 2005