Narrative Player: Reviving Data Narratives with Visuals
Zekai Shao, Leixian Shen, Haotian Li, Yi Shan, Huamin Qu, Yun Wang,, Siming Chen

TL;DR
Narrative Player is a novel system that automatically creates engaging data videos by transforming data narratives into visual sequences with animations and narration, enhancing comprehension and engagement in data-rich documents.
Contribution
It introduces a method that combines large language models, optimization, and text-to-speech to generate coherent data videos from paragraphs and data tables.
Findings
Data videos improved reading experience according to user feedback.
The system effectively characterizes clauses and extracts data facts.
Generated visualizations and animations were well-received by participants.
Abstract
Data-rich documents are commonly found across various fields such as business, finance, and science. However, a general limitation of these documents for reading is their reliance on text to convey data and facts. Visual representation of text aids in providing a satisfactory reading experience in comprehension and engagement. However, existing work emphasizes presenting the insights of local text context, rather than fully conveying data stories within the whole paragraphs and engaging readers. To provide readers with satisfactory data stories, this paper presents Narrative Player, a novel method that automatically revives data narratives with consistent and contextualized visuals. Specifically, it accepts a paragraph and corresponding data table as input and leverages LLMs to characterize the clauses and extract contextualized data facts. Subsequently, the facts are transformed into a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Visualization and Analytics
