Abstract
This paper describes RUCIR’s system in NTCIR-14 Short Text Conversation (STC) Chinese Emotional Conversation Generation (CECG) subtask. In our system, we use the Attention-based Sequence-to-Sequence (Seq2Seq) method as our basic structure to generate emotional responses. This paper introduces (1) an emotion-aware Seq2Seq model and (2) several features to boost the performance of emotion consistency. Official results show that our model performs the best in terms of the overall results across the five given emotion categories.
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Notes
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Here is just for the convenience of explanation, because the sum of two probability may be greater than 1. Actually, we will guarantee the value is not greater than 1.
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Acknowledgements
Zhicheng Dou is the corresponding author. This work was supported by National Key R&D Program of China No. 2018YFC0830703, National Natural Science Foundation of China No. 61872370, and the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China No. 2112018391.
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Li, X., Liu, J., Zheng, W., Wang, X., Zhu, Y., Dou, Z. (2019). A Hybrid Framework of Emotion-Aware Seq2Seq Model for Emotional Conversation Generation. In: Kato, M., Liu, Y., Kando, N., Clarke, C. (eds) NII Testbeds and Community for Information Access Research. NTCIR 2019. Lecture Notes in Computer Science(), vol 11966. Springer, Cham. https://doi.org/10.1007/978-3-030-36805-0_12
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