Rational accounts of language use such as the uniform information density hypothesis, which asserts that speakers distribute information uniformly across their utterances, and the rational speech act (RSA) model, which suggests that speakers optimize the formulation of their message by reasoning about what the comprehender would understand, have been hypothesized to account for a wide range of language use phenomena. We here specifically focus on the production of discourse connectives. While there is some prior work indicating that discourse connective production (...) may be governed by RSA, that work uses a strongly gamified experimental setting. In this study, we aim to explore whether speakers reason about the interpretation of their conversational partner also in more realistic settings. We thereby systematically vary the task setup to tease apart effects of task instructions and effects of the speaker explicitly seeing the interpretation alternatives for the listener. Our results show that the RSA-predicted effect of connective choice based on reasoning about the listener is only found in the original setting where explicit interpretation alternatives of the listener are available for the speaker. The effect disappears when the speaker has to reason about listener interpretations. We furthermore find that rational effects are amplified by the gamified task setting, indicating that meta-reasoning about the specific task may play an important role and potentially limit the generalizability of the found effects to more naturalistic every-day language use. (shrink)

The general principles of perceptuo-motor processing and memory give rise to theNow-or-Never bottleneckconstraint imposed on the organization of the language processing system. In particular, the Now-or-Never bottleneck demands an appropriate structure of linguistic input and rapid incorporation of both linguistic and multisensory contextual information in a progressive, integrative manner. I argue that the emerging predictive processing framework is well suited for the task of providing a comprehensive account of language processing under the Now-or-Never constraint. Moreover, this framework presents a stronger (...) alternative to theChunk-and-Passaccount proposed by Christiansen and Chater (2016), as it better accommodates the available evidence concerning the role of context (in both the narrow and wider senses) in language comprehension at various levels of linguistic representation. Furthermore, the predictive processing approach allows for treating language as a special case of domain-general processing strategies, suggesting deep parallels with other cognitive processes such as vision. (shrink)