Language Comprehension in a Noisy Channel to Changing Situations and Individual Users
The central goal of project A4 is to examine how noise (or the effect of reduced hearing ability) will influence language comprehension, and how natural language generation systems can adapt their output to minimize the risk of misunderstanding. The experimental part of the project investigates neurophysiological correlates of bottom-up perceptual level and top-down predictive language processing, and how these functions interact when noise is added to the signal.
In the modelling part, we propose a noisy channel model, consisting of a component that models comprehension at different levels of hearing ability (based on insights from the experimental part of the project), and a generation component that optimizes the system-generated output in order to minimize the risk of misunderstanding, while also adapting the output to a target channel capacity.
Keywords: ID and channel capacity, language comprehension, aging, dual tasking, driving simulation, natural language generation, dialog systems, psycholinguistics
Other Area-A Projects
- Neurobehavioural Correlates of Surprisal in Online Comprehension A1
- Modelling the Information Density of Event Sequences in Texts A3
- The Role of Language Experience and Visual Context in Surprisal A5
- The Role of Semantic Surprisal for Memory Formation and Retrieval A6
- Controlling Information Density in Discourse Generation A7