A variational approach for estimating vocal tract shapes from the speech signal

This paper presents a novel approach to recovering articulatory trajectories from the speech signal using a variational calculus method and Maeda’s articulatory model. The acoustic-toarticulatory mapping is generally assessed by a double criterion: the acoustic proximity of results to acoustic data and the smoothness of articulatory trajectories. Most of the existing methods are unable to exploit the two criteria simultaneously or at least at the same level. On the other hand, our variational calculus approach combines the two criteria simultaneously and ensures the global acoustic and articulatory consistency without further optimization. This method gives rise to an iterative process which optimizes a startup solution given by an improved lookup algorithm. Codebooks generated with an articulatory model show nonuniform sampling of the acoustic space due to nonlinearities of the acoustic-to-articulatory mapping. We therefore designed an improved lookup algorithm building realistic articulatory trajectories which are not necessarily defined throughout the speech signal.