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Window transformer for dialogue document: a joint framework for causal emotion entailment

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Abstract

The Causal Emotion Entailment (CEE) task aims to extract all potential pairs of emotions and corresponding causes from the unannotated emotion document in the conversational context. Most existing methods to solve CEE task follow a two-stage pipeline framework, in which the first stage is to identify emotional clauses and cause clauses and extract clause representation,separately. And in the second stage is to construct the final emotion and cause pairs. However, they ignore the effect of the distance between clauses on emotion-cause pair matching. Here, we construct a joint framework with Window Transformer to handle this problem. The pre-trained BERT and RoBERTa are used as the text encoder to generate a local representation of clauses in a given document. Meanwhile, we feed it into 2D Window Transformer to make the clause representation sensitive to the context within the Window and to obtain the dependencies between clauses. At the same time, the document ranks the candidate clauses to extract causal emotion entailments, which enhances the representation of clause pairs (emotion pairs and cause pairs) by kernel-based relative position embedding. Experimental results indicate that the framework acquires state-of-the-art results on the benchmark dataset.

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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Acknowledgements

The authors would like to respect and thank all reviewers for their constructive and helpful review. This research is funded by the National Natural Science Foundation of China (62106136, 61902231), Natural Science Foundation of Guangdong Province (2019A1515010943), The Basic and Applied Basic Research of Colleges and Universities in Guangdong Province (Special Projects in Artificial Intelligence)(2019KZDZX1030), 2020 Li Ka Shing Foundation Cross-Disciplinary Research Grant (2020LKSFG04D), and Science and Technology Major Project of Guangdong Province (STKJ2021005).

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  1. Department of Computer Science, Shantou University, Shantou, China

    Dazhi Jiang, Hao Liu, Geng Tu & Runguo Wei

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  1. Dazhi Jiang
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Correspondence to Runguo Wei.

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Jiang, D., Liu, H., Tu, G. et al. Window transformer for dialogue document: a joint framework for causal emotion entailment. Int. J. Mach. Learn. & Cyber. 14, 2697–2707 (2023). https://doi.org/10.1007/s13042-023-01792-y

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