Analysing Human Strategies of Information Transmission as a Function of Discourse Context

Open Access
Authors
Publication date 2021
Host editors
  • A. Bisazza
  • O. Abend
Book title The 25th Conference on Computational Natural Language Learning
Book subtitle CoNLL 2021 : proceedings of the conference : November 10-11, 2021, online
ISBN (electronic)
  • 9781955917056
Event 25th Conference on Computational Natural Language Learning
Pages (from-to) 647–660
Publisher Stroudsburg, PA: The Association for Computational Linguistics
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
Speakers are thought to use rational information transmission strategies for efficient communication (Genzel and Charniak, 2002; Aylett and Turk, 2004; Jaeger and Levy, 2007). Previous work analysing these strategies in sentence production has failed to take into account how the information content of sentences varies as a function of the available discourse context. In this study, we estimate sentence information content within discourse context. We find that speakers transmit information at a stable rate—i.e., rationally—in English newspaper articles but that this rate decreases in spoken open domain and written task-oriented dialogues. We also observe that speakers’ choices are not oriented towards local uniformity of information, which is another hypothesised rational strategy. We suggest that a more faithful model of communication should explicitly include production costs and goal-oriented rewards.
Document type Conference contribution
Note With supplementary video and software
Language English
Published at https://doi.org/10.18653/v1/2021.conll-1.50
Downloads
2021.conll-1.50 (Final published version)
Supplementary materials
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