An adaptive neural control scheme for articulatory synthesis of CV sequences

Reproducing the smooth vocal tract trajectories is critical for high quality articulatory speech synthesis. This paper presents an adaptive neural control scheme based on fuzzy logic and neural networks. The control scheme estimates motor commands from trajectories of flesh-points on selected articulators. These motor commands are then used to reproduce the trajectories based on 2nd order dynamical systems for the underlying articulators. Experiments show that the control scheme is able to manipulate the mass-spring based elastic tract walls in a 2-D articulatory synthesizer to realize efficient speech motor control. In particular, the proposed controller achieves high accuracy during on-line tracking of the lips, the tongue, and the jaw in the simulation of consonant-vowel sequences. It also offers salient features such as generality and adaptability for future developments of control models in articulatory synthesis.