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        <title>Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment</title>
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            <namePart type="given">Shruti</namePart>
            <namePart type="family">Rijhwani</namePart>
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    <abstract>Current models of dialogue mainly focus on utterances within a topically coherent discourse segment, rather than new-topic utterances (NTUs), which begin a new topic not correlating with the content of prior discourse. As a result, these models may sufficiently account for discourse context of task-oriented but not social conversations. We conduct a pilot annotation study of NTUs as a first step towards a model capable of rationalizing conversational coherence in social talk. We start with the naturally occurring social dialogues in the Disco-SPICE corpus, annotated with discourse relations in the Penn Discourse Treebank and Cognitive approach to Coherence Relations frameworks. We first annotate content-based coherence relations that are not available in Disco-SPICE, and then heuristically identify NTUs, which lack a coherence relation to prior discourse. Based on the interaction between NTUs and their discourse context, we construct a classification for NTUs that actually convey certain non-topical coherence in social talk. This classification introduces new sequence-based social intents that traditional taxonomies of speech acts do not capture. The new findings advocates the development of a Bayesian game-theoretic model for social talk.</abstract>
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%0 Conference Proceedings
%T Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment
%A Luu, Alex
%A Malamud, Sophia A.
%Y Rijhwani, Shruti
%Y Liu, Jiangming
%Y Wang, Yizhong
%Y Dror, Rotem
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F luu-malamud-2020-non
%X Current models of dialogue mainly focus on utterances within a topically coherent discourse segment, rather than new-topic utterances (NTUs), which begin a new topic not correlating with the content of prior discourse. As a result, these models may sufficiently account for discourse context of task-oriented but not social conversations. We conduct a pilot annotation study of NTUs as a first step towards a model capable of rationalizing conversational coherence in social talk. We start with the naturally occurring social dialogues in the Disco-SPICE corpus, annotated with discourse relations in the Penn Discourse Treebank and Cognitive approach to Coherence Relations frameworks. We first annotate content-based coherence relations that are not available in Disco-SPICE, and then heuristically identify NTUs, which lack a coherence relation to prior discourse. Based on the interaction between NTUs and their discourse context, we construct a classification for NTUs that actually convey certain non-topical coherence in social talk. This classification introduces new sequence-based social intents that traditional taxonomies of speech acts do not capture. The new findings advocates the development of a Bayesian game-theoretic model for social talk.
%R 10.18653/v1/2020.acl-srw.17
%U https://aclanthology.org/2020.acl-srw.17
%U https://doi.org/10.18653/v1/2020.acl-srw.17
%P 118-133

Markdown (Informal)

[Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment](https://aclanthology.org/2020.acl-srw.17) (Luu & Malamud, ACL 2020)

• Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment (Luu & Malamud, ACL 2020)

ACL

• Alex Luu and Sophia A. Malamud. 2020. Non-Topical Coherence in Social Talk: A Call for Dialogue Model Enrichment. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 118–133, Online. Association for Computational Linguistics.