Skip to main content

EDTree: Emotional Dialogue Trees for Game Based Training.

Collins, J., Hisrt, W., Tang, W., Luu, C., Smith, P., Watson, A and Sahandi, R., 2016. EDTree: Emotional Dialogue Trees for Game Based Training. In: Edutainment 2016, 15-17 April 2016, Hangzhou, China, 77-84.

Full text available as:

EDTree-Emotional Dialogue Trees for Game.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1007/978-3-319-40259-8_7


Immersion and interactivity are a major focus when creat- ing gaming applications, as technology has improved and enabled the creation of larger and more detailed virtual environments the need for more engaging NPCs (non-playable characters) is also required. Many games utilise a form of dialogue tree when conversing with characters within a gaming application, allowing the user to choose their question- s/responses. While this method does provide a dynamic conversation system, it is quite a one-sided level of interactivity with the NPC simply responding to the current question without it a ecting the conversation on a whole. We present a novel dialogue system that explores the emo- tional state of the NPC to provide a more complex form of dialogue tree, termed EDTree (Emotional Dialogue Tree). Based on user actions, the interactions between the user and the NPC are enriched by the emo- tional state of the NPC. Utilising this system will provide an immersive experience based around improved believability of virtual characters. To demonstrate the e ectiveness of our approach, we show an example of a training system that explores the use of gaming technology and the proposed EDTree.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Collins J. et al. (2016) EDTree: Emotional Dialogue Trees for Game Based Training. In: El Rhalibi A., Tian F., Pan Z., Liu B. (eds) E-Learning and Games. Edutainment 2016. Lecture Notes in Computer Science, vol 9654. Springer, Cham
Group:Faculty of Science & Technology
ID Code:27441
Deposited By: Symplectic RT2
Deposited On:01 Mar 2017 12:22
Last Modified:14 Mar 2022 14:03


Downloads per month over past year

More statistics for this item...
Repository Staff Only -