Multiple Approaches to Robust Speech Recognition

Abstract

This paper compares several different approaches to robust speech recognition. We review CMU's ongoing research in the use of acoustical pre-processing to achieve robust speech recognition, and we present the results of the first evaluation of pre- processing in the context of the DARPA standard ATIS domain for spoken language systems. We also describe and compare the effectiveness of three complementary methods of signal processing for robust speech recognition: acoustical pre-processing, microphone array processing, and the use of physiologically- motivated models of peripheral signal processing. Recognition error rates are presented using these three approaches in isolation and in combination with each other for the speaker-independent continuous alphanumeric census speech recognition task.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADA458653

Entities

People

  • Alejandro Acero
  • Fu-hua Liu
  • Richard M. Stern
  • Thomas M. Sullivan
  • Yoshiaki Ohshima

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acoustics
  • Algorithms
  • Automated Speech Recognition
  • Computer Programs
  • Computer Science
  • Computers
  • Cross Correlation
  • Databases
  • Detectors
  • Errors
  • Filtration
  • Language
  • Linear Filtering
  • Noise
  • Recognition
  • Signal Processing
  • Speech

Readers

  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation