TY - CHAP

T1 - Integrating Common Ground and Informativeness in Pragmatic Word Learning

AU - Bohn, Manuel

AU - Tessler, Michael Henry

AU - Frank, Michael C.

N1 - Funding Information: MB received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 749229. MCF was supported by a Jacobs Foundation Advanced Research Fellowship and NSF #1456077. Funding Information: MB received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 749229. MCF was supported by a Jacobs Foundation Advanced Research Fellowship and NSF #1456077. Publisher Copyright: © Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019.All rights reserved.

PY - 2019

Y1 - 2019

N2 - Pragmatic inferences are an integral part of language learning and comprehension. To recover the intended meaning of an utterance, listeners need to balance and integrate different sources of contextual information. In a series of experiments, we studied how listeners integrate general expectations about speakers with expectations specific to their interactional history with a particular speaker. We used a Bayesian pragmatics model to formalize the integration process. In Experiments 1 and 2, we replicated previous findings showing that listeners make inferences based on speaker-general and speaker-specific expectations. We then used the empirical measurements from these experiments to generate model predictions about how the two kinds of expectations should be integrated, which we tested in Experiment 3. Experiment 4 replicated and extended Experiment 3 to a broader set of conditions. In both experiments, listeners based their inferences on both types of expectations. We found that model performance was also consistent with this finding; with better fit for a model which incorporated both general and specific information compared to baselines incorporating only one type. Listeners flexibly integrate different forms of social expectations across a range of contexts, a process which can be described using Bayesian models of pragmatic reasoning.

AB - Pragmatic inferences are an integral part of language learning and comprehension. To recover the intended meaning of an utterance, listeners need to balance and integrate different sources of contextual information. In a series of experiments, we studied how listeners integrate general expectations about speakers with expectations specific to their interactional history with a particular speaker. We used a Bayesian pragmatics model to formalize the integration process. In Experiments 1 and 2, we replicated previous findings showing that listeners make inferences based on speaker-general and speaker-specific expectations. We then used the empirical measurements from these experiments to generate model predictions about how the two kinds of expectations should be integrated, which we tested in Experiment 3. Experiment 4 replicated and extended Experiment 3 to a broader set of conditions. In both experiments, listeners based their inferences on both types of expectations. We found that model performance was also consistent with this finding; with better fit for a model which incorporated both general and specific information compared to baselines incorporating only one type. Listeners flexibly integrate different forms of social expectations across a range of contexts, a process which can be described using Bayesian models of pragmatic reasoning.

KW - Psychology

KW - Bayesian models

KW - Common ground

KW - Pragmatics

KW - Word learning

UR - http://www.scopus.com/inward/record.url?scp=85118512776&partnerID=8YFLogxK

M3 - Article in conference proceedings

SN - 978-099119677-7

SN - 0991196775

SP - 152

EP - 158

BT - Proceedings of the 41st Annual Meeting of the Cognitive Science Society

PB - The Cognitive Science Society

ER -