arXiv Open Access 2023

WonderFlow: Narration-Centric Design of Animated Data Videos

Yun Wang Leixian Shen Zhengxin You Xinhuan Shu Bongshin Lee +3 lainnya
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Abstrak

Creating an animated data video enriched with audio narration takes a significant amount of time and effort and requires expertise. Users not only need to design complex animations, but also turn written text scripts into audio narrations and synchronize visual changes with the narrations. This paper presents WonderFlow, an interactive authoring tool, that facilitates narration-centric design of animated data videos. WonderFlow allows authors to easily specify a semantic link between text and the corresponding chart elements. Then it automatically generates audio narration by leveraging text-to-speech techniques and aligns the narration with an animation. WonderFlow provides a visualization structure-aware animation library designed to ease chart animation creation, enabling authors to apply pre-designed animation effects to common visualization components. It also allows authors to preview and iteratively refine their data videos in a unified system, without having to switch between different creation tools. To evaluate WonderFlow's effectiveness and usability, we created an example gallery and conducted a user study and expert interviews. The results demonstrated that WonderFlow is easy to use and simplifies the creation of data videos with narration-animation interplay.

Topik & Kata Kunci

Penulis (8)

Y

Yun Wang

L

Leixian Shen

Z

Zhengxin You

X

Xinhuan Shu

B

Bongshin Lee

J

John Thompson

H

Haidong Zhang

D

Dongmei Zhang

Format Sitasi

Wang, Y., Shen, L., You, Z., Shu, X., Lee, B., Thompson, J. et al. (2023). WonderFlow: Narration-Centric Design of Animated Data Videos. https://arxiv.org/abs/2308.04040

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Tahun Terbit
2023
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en
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arXiv
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Open Access ✓