A comparison of interfaces in choice driven games : Investigating possible future applications of NLIs in choice driven games by comparing a menu- based interface with an NLI in a text-based game

University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

Author: Jaldeep Acharya; Ludvig Fröberg; [2016]

Keywords: ;

Abstract: Natural language processing has for a long time been a field of research and has been regarded as a thing of the future. Due to its complexity it stopped being featured in computer games in the early 2000s. It has however had a recent revival as a consequence of advancements made in speech recognition, making the possible applications of natural language processing much larger. One market that hasn’t seen much in the way of natural language interfaces recently is that of computer games. This report covers the basics of natural language processing needed to implement two versions of a simple text-based adventure game, one with a menu-based interface and one with a natural lan- guage interface. These were then played by a test group from which usability statistics were gathered to determine if it is likely that NLP will find its way back in to choice driven games in the future. The results showed that even though the menu-based interface has a faster rate of progression, the NLI version of the game was perceived as more enjoyable by users with experience in gaming. The reason being that the NLI al- lowed for more thinking on the user’s part and therefore the game presented a greater challenge, something that is perceived as attractive by users with experience in com- puter games. Also the measured usability was roughly the same for both interfaces while it was feared that it would be much lower for NLIs. Therefore, the conclusion was that it is highly plausible that NLI will find its way back into the gaming world, since it adds a new dimension to adventure games, which is something that attracts users. However, this is given that NLP development continues in the same fast pace as it is today, making it possible to implement a more accurate NLI. 

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