Virtual Standardized Patients for Interactive Conversational Training: A Grand Experiment and New Approach (Chapter 3)

Abstract

The USC Standard Patient is a virtual human-based conversational agent serving in the role of a simulated medical patient, also known as a virtual standardized patient (VSP). This research identified deficiencies of extant VSP systems, defined a robust set of requirements, and successfully achieved nearly all of them. Markedly impressive advancements were made in virtual human technology, techniques to apply natural language processing, automated assessment artificial intelligence, and pedagogical design. The effort succeeded with performance parameters of high conversational performance, accurate assessment, and strongly demonstrated user training effect. Although working well within its confined are of expertise, the ability for computers to create authentic mixed initiative conversations remains elusive. This effort leaves behind many lessons for interactive serious games, clinical virtual humans, and conversational virtual human training applications.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2019
Accession Number
AD1154781

Entities

People

  • Albert S. Rizzo
  • Thomas B. Talbot

Organizations

  • McMaster University
  • University of Southern California

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automated Speech Recognition
  • California
  • Computational Linguistics
  • Computational Science
  • Computer Science
  • Computers
  • Dialogue Systems
  • Health Services
  • Information Science
  • Language
  • Medical Personnel
  • Natural Language Processing
  • Natural Language Understanding
  • Psychology
  • Recognition
  • Reliability
  • United States
  • Virtual Reality

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Oncology
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation
  • AI & ML - Neural Networks