Application of a Back-Propagation Neural Network to Isolated-Word Speech Recognition

Abstract

The primary objective of this research is to explore how a back- propagation neural network (BNN) can be applied to isolated-word speech recognition. Simulation results show that a BNN provides an effective approach for small vocabulary systems. The recognition rate reaches 100% for a 5-word system and 94% for a 10-word system. The general techniques developed in this thesis can be further extended to other applications, such as sonar target recognition, missile seeking and tracking functions in modern weapon systems, and classification of underwater acoustic signals.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1993
Accession Number
ADA272495

Entities

People

  • Chau G. Le

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Signals
  • Automated Speech Recognition
  • California
  • Classification
  • Computers
  • Electrical Engineering
  • Engineering
  • Feature Extraction
  • Geographic Regions
  • Pattern Recognition
  • Recognition
  • Signal Processing
  • Simulations
  • Sonar Targets
  • Target Recognition
  • United States
  • Weapon Systems

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.

Technology Areas

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