A Statistical Approach for Text Processing in Virtual Humans
Anton Leuski, David R. Traum · 2008
We describe a text classification approach based on statistical language modeling. We show how this approach can be used for several natural language processing tasks in a virtual human system. Specifically, we show it can applied to language understanding, language generation, and character response selection tasks. We illustrate these applications with some experimental results. 1. natural language understanding (NLU) module that interprets the text of the user’s utterance and converts it into some internal representation; 2. dialog manager (DM) module that analyzes the interpretation and selects the appropriate response; 3. natural language generation (NLG) module that converts the internal representation to the text of the response. 1