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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2308.04040 |
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| _version_ | 1866911909536595968 |
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| author | Wang, Yun Shen, Leixian You, Zhengxin Shu, Xinhuan Lee, Bongshin Thompson, John Zhang, Haidong Zhang, Dongmei |
| author_facet | Wang, Yun Shen, Leixian You, Zhengxin Shu, Xinhuan Lee, Bongshin Thompson, John Zhang, Haidong Zhang, Dongmei |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_04040 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | WonderFlow: Narration-Centric Design of Animated Data Videos Wang, Yun Shen, Leixian You, Zhengxin Shu, Xinhuan Lee, Bongshin Thompson, John Zhang, Haidong Zhang, Dongmei Human-Computer Interaction 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. |
| title | WonderFlow: Narration-Centric Design of Animated Data Videos |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2308.04040 |