Self-, other-, and joint monitoring using forward models
نویسندگان
چکیده
In the psychology of language, most accounts of self-monitoring assume that it is based on comprehension. Here we outline and develop the alternative account proposed by Pickering and Garrod (2013), in which speakers construct forward models of their upcoming utterances and compare them with the utterance as they produce them. We propose that speakers compute inverse models derived from the discrepancy (error) between the utterance and the predicted utterance and use that to modify their production command or (occasionally) begin anew. We then propose that comprehenders monitor other people's speech by simulating their utterances using covert imitation and forward models, and then comparing those forward models with what they hear. They use the discrepancy to compute inverse models and modify their representation of the speaker's production command, or realize that their representation is incorrect and may develop a new production command. We then discuss monitoring in dialogue, paying attention to sequential contributions, concurrent feedback, and the relationship between monitoring and alignment.
منابع مشابه
Dynamics and Regulation of Locomotion of a Human Swing Leg as a Double-Pendulum Considering Self-Impact Joint Constraint
Background:Despite some successful dynamic simulation of self-impact double pendulum (SIDP)-as humanoid robots legs or arms- studies, there is limited information available about the control of one leg locomotion.Objective :The main goal of this research is to improve the reliability of the mammalians leg locomotion and building more elaborated models close to the natural movements, by modelin...
متن کاملA Self-starting Control Chart for Simultaneous Monitoring of Mean and Variance of Simple Linear Profiles
In many processes in real practice at the start-up stages the process parameters are not known a priori and there are no initial samples or data for executing Phase I monitoring and estimating the process parameters. In addition, the practitioners are interested in using one control chart instead of two or more for monitoring location and variability of processes. In this paper, we consider a s...
متن کاملMonthly runoff forecasting by means of artificial neural networks (ANNs)
Over the last decade or so, artificial neural networks (ANNs) have become one of the most promising tools formodelling hydrological processes such as rainfall runoff processes. However, the employment of a single model doesnot seem to be an appropriate approach for modelling such a complex, nonlinear, and discontinuous process thatvaries in space and time. For this reason, this study aims at de...
متن کاملAn Adaptive Approach to Increase Accuracy of Forward Algorithm for Solving Evaluation Problems on Unstable Statistical Data Set
Nowadays, Hidden Markov models are extensively utilized for modeling stochastic processes. These models help researchers establish and implement the desired theoretical foundations using Markov algorithms such as Forward one. however, Using Stability hypothesis and the mean statistic for determining the values of Markov functions on unstable statistical data set has led to a significant reducti...
متن کامل