Understanding and Generating Dialogue between Characters in Stories: Methodology

Written by teleplay | Published 2024/05/09
Tech Story Tags: natural-language-processing | dialogue-generation | storytelling | character-representation | machine-learning | fiction | narrative-understanding | text-generation

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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

Abstract and Intro

Related Works

DIALSTORY Dataset

Proposed Tasks

Methodology

Experiments

Discussion

Future Work

Conclusion

Limitations and References

5 Methodology

We propose to learn representations of different characters and exert them on decoding masked dialogue turns or predicting speakers. In this section, we describe the details of our model. Figure 2 shows the model overview for the DialGen task.

5.1 Character Representation Learning

5.2 Character Representation Utilization

This paper is available on arxiv under CC 4.0 DEED license.


Written by teleplay | From teleplay to technology, we weave a narrative tapestry that dances between writing, CGI, and "action!"
Published by HackerNoon on 2024/05/09