Synthesizing game audio using deep neural networks

McDonagh, Aoife
Lemley, Joseph
Cassidy, Ryan
Corcoran, Peter
McDonagh, Aoife, Lemley, Joseph, Cassidy, Ryan, & Corcoran, Peter. (2018). Synthesizing game audio using deep neural networks. Paper presented at the 2018 IEEE Games, Entertainment, Media Conference (GEM), Galway, Ireland, 15-17 August.
High quality audio plays an important role in gaming, contributing to player immersion during gameplay. Creating audio content which matches overall theme and aesthetic is essential, such that players can become fully engrossed in a game environment. Sound effects must also fit well with visual elements of a game so as not to break player immersion. Producing suitable, unique sound effects requires the use of a wide range of audio processing techniques. In this paper, we examine a method of generating in-game audio using Generative Adversarial Networks, and compare this to traditional methods of synthesizing and augmenting audio.
Institute of Electrical and Electronics Engineers
Publisher DOI
Attribution-NonCommercial-NoDerivs 3.0 Ireland