Towards a New Model of Verbal Monitoring

As all human activities, verbal communication is fraught with errors. It is estimated that humans produce around 16,000 words per day, but the word that is selected for production is not always correct and neither is the articulation always flawless. However, to facilitate communication, it is important to limit the number of errors. This is accomplished via the verbal monitoring mechanism. A body of research over the last century has uncovered a number of properties of the mechanisms at work during verbal monitoring. Over a dozen routes for verbal monitoring have been postulated. However, to date a complete account of verbal monitoring does not exist. In the current paper we first outline the properties of verbal monitoring that have been empirically demonstrated. This is followed by a discussion of current verbal monitoring models: the perceptual loop theory, conflict monitoring, the hierarchical state feedback control model, and the forward model theory. Each of these models is evaluated given empirical findings and theoretical considerations. We then outline lacunae of current theories, which we address with a proposal for a new model of verbal monitoring for production and perception, based on conflict monitoring models. Additionally, this novel model suggests a mechanism of how a detected error leads to a correction. The error resolution mechanism proposed in our new model is then tested in a computational model. Finally, we outline the advances and predictions of the model.