StoryTrans: Non-Parallel Story Author-Style Transfer with Discourse Representations and Content Enhancing

Understand

Non-parallel text style transfer is an important task in natural language generation.

• However, previous studies concentrate on the token or sentence level, such as sentence sentiment and formality transfer, but neglect long style transfer at the discourse level.
• Long texts usually involve more complicated author linguistic preferences such as discourse structures than sentences.
• In this paper, we formulate the task of non-parallel story author-style transfer, which requires transferring an input story into a specified author style while maintaining source semantics.