EAGER: Spy Feet: Natural Language Generation for Games for Girls

University Of California-Santa Cruz, Santa Cruz CA

Investigators

Abstract

This exploratory project examines how techniques for automatically generating dialog contributions and managing dialog can be incorporated into the narrative structures of outdoor role-playing computer games, such as quests and mysteries. The underlying hypothesis is that the effective use of natural language and dialog technologies in interactive games will eventually lead to more compelling and engaging games, appealing to a much wider segment of the population, and usable for a much wider range of educational, assistive and entertainment applications. As a vehicle for testing the team's research ideas, a prototype novel physical-activity based social role-playing mystery game, Spy Feet is implemented, aimed at encouraging physical activity in young women and girls. Spy Feet runs on mobile devices equipped with GPS, and the game world is mapped onto an outdoor environment consisting of paths and landmarks that are used by plot points in the game. Players must walk between landmarks where dialogs with game characters take place or where clues are located, thus covering a significant amount of a natural terrain while playing the game. Spy Feet utilizes a prototype natural language generation engine, Spy-Gen, that dynamically generates dialogue game narrative sequences whose characterizations and interaction style is targeted at young women and girls. Spy Feet uses Spy-Gen to dynamically adapt aspects of game play to the user and her environment in order to explore how such techniques lead to different game play experiences and outcomes.