TY - GEN
T1 - Synthesizing Game Audio Using Deep Neural Networks
AU - McDonagh, Aoife
AU - Lemley, Joseph
AU - Cassidy, Ryan
AU - Corcoran, Peter
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/30
Y1 - 2018/10/30
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10379/16684
UR - https://www.scopus.com/pages/publications/85056989526
U2 - 10.13025/18618
DO - 10.13025/18618
M3 - Conference Publication
T3 - 2018 IEEE Games, Entertainment, Media Conference, GEM 2018
SP - 312
EP - 315
BT - 2018 IEEE Games, Entertainment, Media Conference, GEM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Games, Entertainment, Media Conference, GEM 2018
Y2 - 15 August 2018 through 17 August 2018
ER -