Extended Abstract

Bridging production and comprehension: Toward an integrated computational model of error correction

Authors
  • Shiva Upadhye (University of California, Irvine)
  • Jiaxuan Li (University of California, Irvine)
  • Richard Futrell (University of California, Irvine)

Abstract

Error correction in production and comprehension has traditionally been studied sepa- rately. In real-time communication, however, correction may not only depend on speaker or comprehender-internal preferences, but also the interlocutors’ knowledge of each other’s strategies. We present an integrated computational framework for error correction in both production and comprehension systems. Modeling error correction as Bayesian inference, we propose that both speaker and comprehender’s correction strategies are influenced by their prior expectations about the intended message and their knowledge of a noise monitoring model. Our results indicate that speakers and comprehenders tend to weigh phonological and semantic cues differently, and these different strategies illuminate the asymmetries and potential interactions between the two systems.

Keywords: error correction; Bayesian inference; strategic cue weighting;, error correction, Bayesian inference, strategic cue weighting,

How to Cite:

Upadhye, S., Li, J. & Futrell, R., (2023) “Bridging production and comprehension: Toward an integrated computational model of error correction”, Society for Computation in Linguistics 6(1), 389-391. doi: https://doi.org/10.7275/q7mg-t564

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Published on
01 Jun 2023