Simulating Vocal Imitation in Infants, using a Growth Articulatory Model and Speech Robotics

Abstract

In order to shed lights on the cognitive representations likely to underlie early vocal imitation, we tried to simulate Kuhl and Meltzoff's experiment (1996), using Bayesian robotics and a statistical model of the vocal tract that had been fitted to pre-babblers' actual vocalizations. It was shown that audition is compulsory to account for infants' early vocal imitation performance, inasmuch as the simulation of purely visual imitation failed to reproduce infants' score and pattern of imitation. Further, a small number of vocalizations (less than 100!) appeared to be enough for a learning process to provide scores at least as high as those of pre-babblers. Thus, early vocal imitation lies in the reach of a baby robot, with only a few assumptions about learning and imitation.