REINFORCEMENT-MODULATED SELF-ORGANIZATION IN INFANT MOTOR SPEECH LEARNING

摘要

Neural network models of early motor speech vocal learning are reviewed, with a focus on those models that utilize reinforcement to modulate what would otherwise be self-organized learning. It is argued that such a mechanism likely plays a role in bringing about the changes observed in prespeech vocalizations produced by human infants. Such models complement well the already popular purely self-organized learning models that focus on effects of exposure to sounds from the ambient language.