Makoto Hirayama, Eric Vatikiotis-Bateson, Mitsuo Kawato
Progress ha.s been made in comput.ational implementation of speech production based on physiological dat.a. An inverse dynamics model of the speech articulator's l1111sculo-skeletal system. which is the mapping from art.iculator t.rajectories to e\ectromyogl'aphic (EMG) signals, was modeled using the acquired forward dynamics model and temporal (smoot.hness of EMG activation) and range constraints. This inverse dynamics model allows the use of a faster speech mot.or control scheme, which can be applied to phoneme-to(cid:173) speech synthesis via musclo-skeletal system dynamics, or to future use in speech recognition. The forward acoustic model, which is the mapping from articulator trajectories t.o the acoustic parameters, was improved by adding velocity and voicing information inputs to distinguish acollst.ic paramet.er differences caused by changes in source characterist.ics.