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        <title>Spectral Analysis of Information Density in Dialogue Predicts Collaborative Task Performance</title>
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        <namePart type="given">Yang</namePart>
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            <title>Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)</title>
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            <namePart type="given">Regina</namePart>
            <namePart type="family">Barzilay</namePart>
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    <abstract>We propose a perspective on dialogue that focuses on relative information contributions of conversation partners as a key to successful communication. We predict the success of collaborative task in English and Danish corpora of task-oriented dialogue. Two features are extracted from the frequency domain representations of the lexical entropy series of each interlocutor, power spectrum overlap (PSO) and relative phase (RP). We find that PSO is a negative predictor of task success, while RP is a positive one. An SVM with these features significantly improved on previous task success prediction models. Our findings suggest that the strategic distribution of information density between interlocutors is relevant to task success.</abstract>
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    <identifier type="doi">10.18653/v1/P17-1058</identifier>
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%0 Conference Proceedings
%T Spectral Analysis of Information Density in Dialogue Predicts Collaborative Task Performance
%A Xu, Yang
%A Reitter, David
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F xu-reitter-2017-spectral
%X We propose a perspective on dialogue that focuses on relative information contributions of conversation partners as a key to successful communication. We predict the success of collaborative task in English and Danish corpora of task-oriented dialogue. Two features are extracted from the frequency domain representations of the lexical entropy series of each interlocutor, power spectrum overlap (PSO) and relative phase (RP). We find that PSO is a negative predictor of task success, while RP is a positive one. An SVM with these features significantly improved on previous task success prediction models. Our findings suggest that the strategic distribution of information density between interlocutors is relevant to task success.
%R 10.18653/v1/P17-1058
%U https://aclanthology.org/P17-1058
%U https://doi.org/10.18653/v1/P17-1058
%P 623-633

Markdown (Informal)

[Spectral Analysis of Information Density in Dialogue Predicts Collaborative Task Performance](https://aclanthology.org/P17-1058) (Xu & Reitter, ACL 2017)

• Spectral Analysis of Information Density in Dialogue Predicts Collaborative Task Performance (Xu & Reitter, ACL 2017)

ACL

• Yang Xu and David Reitter. 2017. Spectral Analysis of Information Density in Dialogue Predicts Collaborative Task Performance. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 623–633, Vancouver, Canada. Association for Computational Linguistics.