Jerk Minimization for Acoustic-To-Articulatory Inversion

The effortless speech production in humans requires coordinated movements of the articulators such as lips, tongue, jaw, velum, etc. Therefore, measured trajectories obtained are smooth and slowly-varying. However, the trajectories estimated from acoustic-to-articulatory inversion (AAI) are found to be jagged . Thus, energy minimization is used as smoothness constraint for improving performance of the AAI. Besides energy minimization, jerk (i.e., rate of change of acceleration) is known for quantification of smoothness in case of human motor movements. Human motors are organized to achieve intended goal with smoothest possible movements, under the constraint of minimum accelerative transients. In this paper, we propose jerk minimization as an alternative smoothness criterion for frame-based acoustic-to-articulatory inversion. The resultant trajectories obtained are smooth in the sense that for articulator-specific window size, they will have minimum jerk. The results using this criterion were found to be comparable with inversion schemes based on existing energy minimization criteria for achieving smoothness.