Emotional Variation in Speech-Based Natural Language Generation

Abstract

We present a framework for handling emotional variations in a speech-based natural language system for use in the MRE virtual training environment. The system is a first step toward addressing issues in emotion-based modeling of verbal communicative behavior. We cast the problem of emotional generation as a distance minimization task, in which the system chooses between multiple valid realizations for a given input based on the emotional distance of each realization from the speakers attitude toward that input.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2014
Accession Number
AD1170914

Entities

People

  • Eduard Hovy
  • Michael Fleischman

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automated Speech Recognition
  • Autonomous Agents
  • Cognitive Science
  • Collisions
  • Computational Linguistics
  • Computational Science
  • Demographic Cohorts
  • Education
  • Environment
  • Expert Systems
  • Generators
  • Human Behavior
  • Information Science
  • Intelligence Community
  • Language
  • Linguistics
  • Natural Language Processing
  • Natural Languages
  • Personality
  • Training
  • Virtual Reality

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Control Systems Engineering.