Spire Based Speaker-Independent Continuous Speech Recognition Using Mixed Feature Sets.

Abstract

A system was developed to investigate continuous speech recognition. The system incorporates multiple features and dynamic programming to recognize continuous inputs of the spoken digits (zero through nine). The fundamental design concept extends from previous successful recognition research efforts involving both isolated and continuous speech using multiple feature sets, multiple template sets, and dynamic programming. Among the features used in the investigation are wide band spectrogram, narrow band spectrogram, linear predictive coding (LPC) coefficients, LPC spectrum, frication frequency, and format tracks. An advanced speech research tool called SPIRE provided the computational functions needed to extract the raw features. Keywords: Theses; Speech analysis.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1987
Accession Number
ADA188834

Entities

People

  • Robert G. Dawson

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automated Speech Recognition
  • Band Spectra
  • Computer Programming
  • Computers
  • Dynamic Programming
  • Electrical Engineering
  • Frequency
  • High Level Language Architecture
  • Language
  • Lisp Programming Language
  • Operating Systems
  • Recognition
  • Speech Analysis
  • Template Patterns
  • Two Dimensional
  • Word Recognition

Readers

  • Computational Modeling and Simulation
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML