Abstract
Electropalatography is a well established technique for recording information on the patterns of contact between the tongue and the hard palate during speech, leading to a stream of binary vectors representing contacts or non-contacts between the tongue and certain positions on the hard palate. A data-driven approach to mapping the speech signal onto electropalatographic information is presented. Principal component analysis is used to model the spatial structure of the electropalatographic data and support vector regression is used to map acoustic parameters onto projections of the electropalatographic data on the principal components.
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