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Understanding and Generating Dialogue between Characters in Stories: Conclusion

by Teleplay Technology May 9th, 2024

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Exploring machine understanding of story dialogue via new tasks and dataset, improving coherence and speaker recognition in storytelling AI.

featured image - Understanding and Generating Dialogue between Characters in Stories: Conclusion

Authors:

(1) Jianzhu Yao, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology;

(2) Ziqi Liu, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology;

(3) Jian Guan, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology;

(4) Minlie Huang, The CoAI group, Tsinghua University, Beijing, China Department of Computer Science and Technology, Tsinghua University, Beijing, China Beijing National Research Center for Information Science and Technology.

Table of Links

Limitations and References

9 Conclusion

In this work, we present the first study on understanding and generating inter-character dialogue in stories. To this end, we collect a Chinese story dataset DIALSTORY with a large amount of dialogue, and propose two new tasks including masked dialogue generation and dialogue speaker recognition. We also construct standardized datasets for these tasks through automatic and manual annotations based on DIALSTORY. By incorporating representations of different characters, our model outperforms strong baselines significantly on both tasks in terms of automatic and manual evaluation. The benchmark datasets, tasks, and models will further boost the development of this field.