A Statistical Approach for Text Processing in Virtual Humans

Abstract

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 be applied to language understanding, language generation, and character response selection tasks. We illustrate these applications with some experimental results.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA505848

Entities

People

  • Anton Leuski
  • David R Traum

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Computational Linguistics
  • Computational Science
  • Computer Languages
  • Data Mining
  • Information Retrieval
  • Information Science
  • Language
  • Linguistics
  • Natural Language Processing
  • Natural Language Understanding
  • Natural Languages
  • Ontologies
  • Supervised Machine Learning
  • Trainees

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Regression Analysis.
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation