Automatic Recognition of Speech in Stressful Environments

Abstract

This document describes a body of research conducted for the purpose of improving the performance of automatic speech recognition (ASR) systems in noisy, stressful environments. To accomplish this, several avenues of basic research were investigated. First, novel techniques for noise reduction were developed. Second, three novel robust recognition systems were developed. One of these techniques relied on noise removal, another on linear least squares system identification, and the third on robust distance measures. Third, methods for characterizing stressed speech parametrically were developed. Among the descriptors used were various prosodic features, spectral features, and glottal excitation characteristics. Fourth, methods were developed that were shown to improve ASR performance in noisy or stressed conditions.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1991
Accession Number
ADA242917

Entities

People

  • John H. Hansen
  • Kathleen E. Cummings
  • Mark A. Clements
  • Sungjae Lim

Organizations

  • Human Engineering Laboratory

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Artificial Intelligence
  • Automated Speech Recognition
  • Cognitive Workload
  • Computational Science
  • Databases
  • Electrical Engineering
  • Engineering
  • Hidden Markov Models
  • Human Factors Engineering
  • Identification
  • Information Science
  • Noise Reduction
  • Recognition
  • Signal Processing
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design

Technology Areas

  • AI & ML