Abstract
Electropalatography is a well established technique for recording information on the patterns of contact between the tongue and the hard palate during speech. It leads to a stream of binary vectors, called electropalatograms. We are interested in the mapping from the acoustic signal to electropalatographic information. We present results on experiments using Support Vector Classification and a combination of Principal Component Analysis and Support Vector Regression.
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Toutios, A., Margaritis, K. (2006). On the Acoustic-to-Electropalatographic Mapping. In: Faundez-Zanuy, M., Janer, L., Esposito, A., Satue-Villar, A., Roure, J., Espinosa-Duro, V. (eds) Nonlinear Analyses and Algorithms for Speech Processing. NOLISP 2005. Lecture Notes in Computer Science(), vol 3817. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11613107_16
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DOI: https://doi.org/10.1007/11613107_16
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