Cognitive Modelling of Information Density for Discourse Relations
Project B2 investigates rational models of language processing at the level of coherence relations. A central aim of the project is to jointly model the likelihood of communicative success (conveying the intended relation) and the linguistic encoding of a discourse relation in terms of connective choice (or omission of an explicit connective).
To this end, we explore the relationship between the uniform information density hypothesis and pragmatic rational models of communication, such as the rational speech act model (RSA). A modeling bottleneck lies in the small amount of training data for building automatic discourse relation parsers that can estimate discourse relation surprisal. This will be addressed using crowd-sourced annotations, as well as machine learning methods that enable us to exploit additional weaker signals from related tasks and explicitation of coherence relations during human translation.
Keywords: psycholinguistics, computational modelling, discourse relations
Other Area-B Projects
- Information Density in English Scientific Writing: A Diachronic Perspective B1
- Information Theory and Ellipsis Redundancy B3
- Modeling and Measuring Information Density B4
- Neural Feature and Representation Learning for Information Density Based Translationese Classification B6
- Modelling Human Translation with a Noisy Channel B7