E-ffective: a visual analytic system for exploring the emotion andeffectiveness of inspirational speeches

Maher, Kevin, Huang, Zeyuan, Song, Jiancheng, Deng, Xiaoming, Lai, Yukun ORCID: https://orcid.org/0000-0002-2094-5680, Ma, Cuixia, Wang, Hao, Liu, Yong-Jin and Wang, Hongan 2022. E-ffective: a visual analytic system for exploring the emotion andeffectiveness of inspirational speeches. IEEE Transactions on Visualization and Computer Graphics 28 (1) , pp. 508-517. 10.1109/TVCG.2021.3114789

PDF - Accepted Post-Print Version Download (4MB)

Abstract

What makes speeches effective has long been a subject for debate, and until today there is broad controversy among public speaking experts about what factors make a speech effective as well as the roles of these factors in speeches. Moreover, there is a lack of quantitative analysis methods to help understand effective speaking strategies. In this paper, we propose E-ffective, a visual analytic system allowing speaking experts and novices to analyze both the role of speech factors and their contribution in effective speeches. From interviews with domain experts and investigating existing literature, we identified important factors to consider in inspirational speeches. We obtained the generated factors from multi-modal data that were then related to effectiveness data. Our system supports rapid understanding of critical factors in inspirational speeches, including the influence of emotions by means of novel visualization methods and interaction. Two novel visualizations include E-spiral (that shows the emotional shifts in speeches in a visually compact way) and E-script (that connects speech content with key speech delivery information). In our evaluation we studied the influence of our system on experts' domain knowledge about speech factors. We further studied the usability of the system by speaking novices and experts on assisting analysis of inspirational speech effectiveness.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	1077-2626
Date of First Compliant Deposit:	2 September 2021
Date of Acceptance:	16 July 2021
Last Modified:	25 Nov 2024 02:00
URI:	https://orca.cardiff.ac.uk/id/eprint/143850

Citation Data

Cited 3 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item