Multimodal AI adaptability on an audio exercise game for the visually impaired
Date of Publication
2015
Document Type
Master's Thesis
Degree Name
Master of Science in Computer Science
College
College of Computer Studies
Department/Unit
Computer Science
Abstract/Summary
With new modules to interact with a game such as Microsofts Kinect for the Xbox 360 and the Nintendo Wii, games have begun to introduce more complex inputs. These inputs are usually used for games that will require body movements. As such, exercise games were developed and because the inputs are simple even those with great sight impairment would now be able to play the game. This technology has the potential to be used for developing games for the disabled sector as well, particularly the visually impaired due to its non-reliance on controllers. Through the years games specifically designed for the visually impaired has been increasing in development as well.
This research created an AI opponent designed for the visually impaired that will give the player a higher sense of enjoyment and increase the games playability. The AI opponent constructed would adapt to the players behaviors while keeping the game playable and winnable by the visually impaired players with results showing that adaptation increases the games playability. In the process it will be possible to create a heuristic guideline on how to create audio exercise games for the visually impaired. How visually impaired gamers view and react against AI opponents as compared to sighted players was also made apparent. The visually impaired and sighted players had the same viewpoint on certain aspects but of course there were differences as well. These differences on views include winning and losing, challenges, level of difficulty, and replayability of the game.
Abstract Format
html
Language
English
Format
Electronic
Accession Number
CDTG005979
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
1 computer optical disc ; 4 3/4 in.
Recommended Citation
Malonzo, E. (2015). Multimodal AI adaptability on an audio exercise game for the visually impaired. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/4844