A neural understanding of speech motor learning

Speech motor learning is still an under-discussion process in neural computational modeling. In this paper we focus on the relationship between vowel articulation and its muscle activation patterns, propose a neural understanding of speech motor learning and elucidate the neural strategy for speech learning of infants. An existing physiological model including speech articulator organs which has successfully replicated the biomechanical articulatory movement has been used. Self-organizing map related to the contour positions of control points and muscle activation patterns was established during speech motor learning. Experimental result refer to the one-to-many problem in the mapping between the high-level to the low-level motor states, which indicates that quite different muscle activation patterns can lead to similar articulatory positions.