Tongue shape conversion with non-parallel training data

Articulatory data is an indispensable resource for speech production research. It will facilitate this study if we can convert one speaker´s articulatory data to adapt a given target speaker. In this paper, we propose a tongue shape conversion method for nonparallel training data. The method combines thin-plate spline approximation (TPSA) algorithm with codebook mapping. The TPSA is a spatial morph method with landmarks extracted from articulatory data with phonetic segmentations. The landmarks´ degree of certainty is evaluated and be considered in the TPSA morph. The proposed method has the advantages of the spatial morph and the codebook mapping by considering both the spatial configuration and the acoustic parameters. The results of our experiments with electromagnetic articulography (EMA) data indicate that the proposed method yields better results than the spatial morph method and the codebook mapping regardless the amount of training data.