[CaCL] CaCL 3/23: A noisy-channel approach to depth-charge illusions (in preparation for Ted Gibson visit)

Oh, Byung-Doh oh.531 at buckeyemail.osu.edu
Fri Mar 17 16:23:26 EDT 2023


Hi everyone,

Next Thursday, we'll discuss the following Cognition article in preparation for Ted Gibson's visit on Friday. It's about modeling the plausibility of depth-charge illusions under the noisy-channel Bayesian inference framework and is directly relevant to his talk.

This work is mostly experimental in nature, so we hope other department members that are interested can also join us for a more fruitful discussion (please include this line in the weekly digest 🙏).

A noisy-channel approach to depth-charge illusions (Zhang et al. 2023)
https://www.sciencedirect.com/science/article/abs/pii/S0010027722003353 (paywalled, please access through OSU Library)
The “depth-charge” sentence, No head injury is too trivial to be ignored, is often interpreted as “no matter how trivial head injuries are, we should not ignore them” while the literal meaning is the opposite – “we should ignore them”. Four decades of research have failed to resolve the source of this entrenched semantic illusion. Here we adopt the noisy-channel framework for language comprehension to provide a potential explanation. We hypothesize that depth-charge sentences result from inferences whereby comprehenders derive the interpretation by weighing the plausibility of possible readings of the depth-charge sentences against the likelihood of plausible sentences being produced with errors. In four experiments, we find that (1) the more plausible the intended meaning of the depth-charge sentence is, the more likely the sentence is to be misinterpreted; and (2) the higher the likelihood of our hypothesized noise operations, the more likely depth-charge sentences are to be misinterpreted. These results suggest that misinterpretation is affected by both world knowledge and the distance between the depth-charge sentence and a plausible alternative, which is consistent with the noisy-channel framework.

Best,
Byung-Doh

=================
Byung-Doh Oh (he/him/his)
Ph.D. Student
Department of Linguistics
The Ohio State University

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.osu.edu/pipermail/cacl/attachments/20230317/2ca9a750/attachment.html>


More information about the CaCL mailing list