Processing open text input in a scripted communication scenario

R. Lala, J.T. Jeuring

Research output: Contribution to conferencePaperAcademic

Abstract

Serious games often employ pre-scripted dialogues and interactions
with a player; in contrast to free user input that enables deeper
immersion. In this paper we explore possibilities for interactive natural
language dialogue in a serious game by combining Natural Language Processing
(NLP) techniques with dialogue management. Our game learning
environment has a communication scenario editor in which a domain
expert develops a structured, scripted scenario as a sequence of potential
interactions. A communication scenario is context-specific and often
follows a protocol - for instance, delivering bad news to a patient. Currently,
a player navigates through a simulation and converses with a
virtual character by choosing a statement option from one of the prescripted
player statements, at each step in the simulation. We develop a
scenario-specific corpus method (SSCM) to process open responses (i.e.
natural language inputs) in our learning environment. We conduct an
experiment to collect data for comparing SSCM against multiple NLP
methods, and another experiment to investigate if framing can improve
processing open-text input using SSCM in a communication simulation.
Original languageEnglish
Publication statusPublished - 9 Nov 2018

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