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Discourse Markers as the Classificatory Factors of Speech Acts

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Chinese Computational Linguistics (CCL 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13603))

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Abstract

Since the debut of the speech act theory, the classification standards of speech acts have been in dispute. Traditional abstract taxonomies seem insufficient to meet the needs of artificial intelligence for identifying and even understanding speech acts. To facilitate the automatic identification of the communicative intentions in human dialogs, scholars have tried some data-driven methods based on speech-act annotated corpora. However, few studies have objectively evaluated those classification schemes. In this regard, the current study applied the frequencies of the eleven discourse markers (oh, well, and, but, or, so, because, now, then, I mean, and you know) proposed by Schiffrin [24] to investigate whether they can be effective indicators of speech act variations. The results showed that the five speech acts of Agreement can be well classified in terms of their functions by the frequencies of discourse markers. Moreover, it was found that the discourse markers well and oh are rather efficacious in differentiating distinct speech acts. This paper indicates that quantitative indexes can reflect the characteristics of human speech acts, and more objective and data-based classification schemes might be achieved based on these metrics.

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Notes

  1. 1.

    For all the clustering results using different methods and distance metrics, see Appendix A.

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Acknowledgements

The authors are grateful to the three anonymous reviewers for providing helpful feedback on this paper.

Author information

Authors and Affiliations

  1. Department of Linguistics, Zhejiang University, Hangzhou, China

    Da Qi, Chenliang Zhou & Haitao Liu

  2. Center for Linguistics and Applied Linguistics, Guangdong University of Foreign Studies, Guangzhou, China

    Haitao Liu

Authors
  1. Da Qi
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  2. Chenliang Zhou
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  3. Haitao Liu
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Corresponding author

Correspondence to Haitao Liu .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Maosong Sun

  2. Tsinghua University, Beijing, China

    Yang Liu

  3. Harbin Institute of Technology, Harbin, China

    Wanxiang Che

  4. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Yang Feng

  5. Fudan University, Shanghai, China

    Xipeng Qiu

  6. Beijing Language and Culture University, Beijing, China

    Gaoqi Rao

  7. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Yubo Chen

Appendix A. The Clustering Results of the Frequencies of Discourse Markers in the Speech Acts of Agreement

Appendix A. The Clustering Results of the Frequencies of Discourse Markers in the Speech Acts of Agreement

(See Fig. 3).

Fig. 3.
figure 3

The clustering results of the frequencies of DMs in the speech acts of Agreement.

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Qi, D., Zhou, C., Liu, H. (2022). Discourse Markers as the Classificatory Factors of Speech Acts. In: Sun, M., et al. Chinese Computational Linguistics. CCL 2022. Lecture Notes in Computer Science(), vol 13603. Springer, Cham. https://doi.org/10.1007/978-3-031-18315-7_1

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  • DOI: https://doi.org/10.1007/978-3-031-18315-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18314-0

  • Online ISBN: 978-3-031-18315-7

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