Seeing [u] aids vocal learning: Babbling and imitation of vowels using a 3D vocal tract model, reinforcement learning, and reservoir computing

We present a model of imitative vocal learning consisting of two stages. First, the infant is exposed to the ambient language and forms auditory knowledge of the speech items to be acquired. Second, the infant attempts to imitate these speech items and thereby learns to control the articulators for speech production. We model these processes using a recurrent neural network and a realistic vocal tract model. We show that vowel production can be successfully learnt by imitation. Moreover, we find that acquisition of [u] is impaired if visual information is discarded during imitation. This might give sighted infants an advantage over blind infants during vocal learning, which is in agreement with experimental evidence.