Abstract
In this paper we introduce Bardo, a real-time intelligent system to automatically select the background music for tabletop role-playing games. Bardo uses an off-the-shelf speech recognition system to transform into text what the players say during a game session, and a supervised learning algorithm to classify the text into an emotion. Bardo then selects and plays as background music a song representing the classified emotion. We evaluate Bardo with a Dungeons and Dragons (D&D) campaign available on YouTube. Accuracy experiments show that a simple Naive Bayes classifier is able to obtain good prediction accuracy in our classification task. A user study in which people evaluated edited versions of the D&D videos suggests that Bardo’s selections can be better than those used in the original videos of the campaign.
Cite
CITATION STYLE
Padovani, R. R., Ferreira, L. N., & Lelis, L. H. S. (2017). Bardo: Emotion-based music recommendation for tabletop role-playing games. In Proceedings of the 13th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2017 (pp. 214–220). AAAI press. https://doi.org/10.1609/aiide.v13i1.12958
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.