Using Adaptive Parsing to Integrate Dialogue Scripts in Game Development

For people without programming experience, integrating their work into the main project forms a common bottleneck in video game development. Particularly for dialogue writing, existing approaches for moving the text into the codebase are either highly tedious or excessively heavyweight for faster paced projects. Given that writers often initially produce loosely-formatted scripts, this thesis describes Game-DAP, an adaptive parsing system that accounts for the variation in individual dialogue writing styles. Examinations of pre-existing systems and a survey conducted on developers form a basis for a syntactic model of the information commonly encapsulated by dialogue scripts. This model lends itself to a design for the parsing process used by Game-DAP, which aims to provide as much flexibility to writers as possible with those assumptions as a baseline. User testing results informed the evaluation of the system, focusing on its accuracy, flexibility, and accessibility from the perspective of various authors. Although this analysis revealed several classes of inputs that Game-DAP struggles to process with full correctness, the more successful cases and instances of positive feedback suggest that a refined approach to this kind of domain-specific parsing could provide great value in the creative writing process of game dialogue.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2024

Author dc:creator

• Taylor, Temi

Advisor dc:contributor.advisor

• Eberhardt, Richard

Statement dc:rights

• Attribution 4.0 International (CC BY 4.0)
• Copyright retained by author(s)

Licence dc:rights.uri

• https://creativecommons.org/licenses/by/4.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/157203

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/157203