Pickering & Garrod's (P&G's) theory could be modified to describe how listeners rapidly incorporate context to generate predictions about speech despite inter-talker variability. However, in order to do so, the content of predicted percepts must be expanded to include phonetic information. Further, the way listeners identify and represent inter-talker differences and subsequently determine which prediction method to use would require further specification.

Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.

Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume (...) that actors construct forward models of their actions before they execute those actions, and that perceivers of others' actions covertly imitate those actions, then construct forward models of those actions. We use these accounts of action, action perception, and joint action to develop accounts of production, comprehension, and interactive language. Importantly, they incorporate well-defined levels of linguistic representation. We show how speakers and comprehenders use covert imitation and forward modeling to make predictions at these levels of representation, how they interweave production and comprehension processes, and how they use these predictions to monitor the upcoming utterances. We show how these accounts explain a range of behavioral and neuroscientific data on language processing and discuss some of the implications of our proposal. (shrink)

Are there individual tendencies in convergence, such that some speakers consistently converge more than others? Similarly, are there natural “leaders,” speakers with whom others converge more? Are such tendencies consistent across different linguistic characteristics? We use the Switchboard Corpus to perform a large‐scale convergence study of speakers in multiple conversations with different interlocutors, across six linguistic characteristics. Because each speaker participated in several conversations, it is possible to look for individual differences in speakers' likelihood of converging and interlocutors' likelihood of (...) eliciting convergence. We only find evidence for individual differences by interlocutor, not by speaker: There are natural leaders of convergence, who elicit more convergence than others across characteristics and across conversations. The lack of similar evidence for speakers who converge more than others suggests that social factors have a stronger effect in mediating convergence than putative individual tendencies in producing convergence, or that such tendencies are characteristic‐specific. (shrink)