A latent-variable modelling approach to the acoustic-to-articulatory mapping problem. I
We present a latent variable approach to the acoustic-toarticulatory mapping problem, where different vocal tract configurations can give rise to the same acoustics. In latent variab le modelling, the combined acoustic and articulatory data are ass umed to have been generated by an underlying low-dimensional proce ss. A parametric probabilistic model is estimated and mappings a re derived from the respective conditional distributions. This as the advantage over other methods, such as articulatory codeboo ks or neural networks, of directly addressing the nonuniqueness problem. We demonstrate our approach with electropalatographi c and acoustic data from the ACCOR database.