Immersive Gameplay via Improved Natural Language Understanding

Abstract

Many first-person shooters feature non-player characters (NPCs) that work alongside the player. Interfacing with these NPCs can add unnecessary complication to a game and steepen the learning curve for new players. Recent improvements in automated voice recognition and language representation have set the stage for more immersive methods of interfacing with NPCs through player speech. In this paper, we present several promising methods of classifying user utterances to extract predefined commands from unstructured speech. This framework facilitates a more flexible interface than has been used in past speech-controlled games. We also show how our methods effectively leverage small sets of example data to outperform existing industrial utterance classification systems.