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        <title>Does Listener Gaze in Face-to-Face Interaction Follow the Entropy Rate Constancy Principle: An Empirical Study</title>
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            <namePart type="given">Houda</namePart>
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            <namePart type="given">Juan</namePart>
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        <name type="personal">
            <namePart type="given">Kalika</namePart>
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    <abstract>It is generally assumed that language (written and spoken) follows the entropy rate constancy (ERC) principle, which states that the information density of a text is constant over time. Recently, this has also been found for nonverbal gestures used in monologue, but it is still unclear whether the ERC principle also applies to listeners’ nonverbal signals. We focus on listeners’ gaze behaviour extracted from video-recorded conversations and trained a transformer-based neural sequence model to process the gaze data of the dialogues and compute its information density. We also compute the information density of the corresponding speech using a pre-trained language model. Our results show (1) that listeners’ gaze behaviour in dialogues roughly follows the ERC principle, as well as (2) a congruence between information density of speech and listeners’ gaze behaviour.</abstract>
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    <identifier type="doi">10.18653/v1/2023.findings-emnlp.1026</identifier>
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%0 Conference Proceedings
%T Does Listener Gaze in Face-to-Face Interaction Follow the Entropy Rate Constancy Principle: An Empirical Study
%A Wang, Yu
%A Buschmeier, Hendrik
%Y Bouamor, Houda
%Y Pino, Juan
%Y Bali, Kalika
%S Findings of the Association for Computational Linguistics: EMNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F wang-buschmeier-2023-listener
%X It is generally assumed that language (written and spoken) follows the entropy rate constancy (ERC) principle, which states that the information density of a text is constant over time. Recently, this has also been found for nonverbal gestures used in monologue, but it is still unclear whether the ERC principle also applies to listeners’ nonverbal signals. We focus on listeners’ gaze behaviour extracted from video-recorded conversations and trained a transformer-based neural sequence model to process the gaze data of the dialogues and compute its information density. We also compute the information density of the corresponding speech using a pre-trained language model. Our results show (1) that listeners’ gaze behaviour in dialogues roughly follows the ERC principle, as well as (2) a congruence between information density of speech and listeners’ gaze behaviour.
%R 10.18653/v1/2023.findings-emnlp.1026
%U https://aclanthology.org/2023.findings-emnlp.1026
%U https://doi.org/10.18653/v1/2023.findings-emnlp.1026
%P 15372-15379

Markdown (Informal)

[Does Listener Gaze in Face-to-Face Interaction Follow the Entropy Rate Constancy Principle: An Empirical Study](https://aclanthology.org/2023.findings-emnlp.1026) (Wang & Buschmeier, Findings 2023)

• Does Listener Gaze in Face-to-Face Interaction Follow the Entropy Rate Constancy Principle: An Empirical Study (Wang & Buschmeier, Findings 2023)

ACL

• Yu Wang and Hendrik Buschmeier. 2023. Does Listener Gaze in Face-to-Face Interaction Follow the Entropy Rate Constancy Principle: An Empirical Study. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 15372–15379, Singapore. Association for Computational Linguistics.