Research Post
In this paper we present Bardo Composer, a system to generate background music for tabletop role-playing games. Bardo Composer uses a speech recognition system to translate player speech into text, which is classified according to a model of emotion. Bardo Composer then uses Stochastic Bi-Objective Beam Search, a variant of Stochastic Beam Search that we introduce in this paper, with a neural model to generate musical pieces conveying the desired emotion.
We performed a user study with 116 participants to evaluate whether people are able to correctly identify the emotion conveyed in the pieces generated by the system. In our study we used pieces generated for Call of the Wild, a Dungeons and Dragons campaign available on YouTube. Our results show that human subjects could correctly identify the emotion of the generated music pieces as accurately as they were able to identify the emotion of pieces written by humans.
Feb 24th 2022
Research Post
Feb 1st 2022
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chairs Neil Burch and Michael Bowling: Rethinking formal models of partially observable multiagent decision making
Dec 6th 2021
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chairs Neil Burch and Micheal Bowling: Player of Games
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