Limited Domain Synthesis of Expressive Military Speech for Animated Characters

Abstract

Text-to-speech synthesis can play an important role in interactive education and training applications, as voices for animated agents. Such agents need high-quality voices capable of expressing intent and emotion. This paper presents preliminary results in an effort aimed at synthesizing expressive military speech for training applications. Such speech has acoustic and prosodic characteristics that can differ markedly from ordinary conversational speech. A limited domain synthesis approach is used employing samples of expressive speech, classified according to speaking style. The resulting synthesizer was tested both in isolation and in the context of a virtual reality training scenario with animated characters.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2002
Accession Number
ADA459395

Entities

People

  • C. Labore
  • M. Bulut
  • R. Whitney
  • Rabindra Das
  • S Narayanan
  • W. L. Johnson

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Abstracts
  • Automated Speech Recognition
  • Background Noise
  • Boundaries
  • Information Operations
  • Information Science
  • Language
  • Lessons Learned
  • Military Training
  • Motor Vehicle Accidents
  • Natural Languages
  • Personality
  • Ratings
  • Trainees
  • Training
  • Vocabulary
  • Waveforms

Readers

  • Computational Linguistics
  • Military Training and Readiness Simulation
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation