Linear Prediction and the Spectral Analysis of Speech

Abstract

The report gives a detailed treatment of the use of linear prediction in speech analysis. New concepts are developed and more familiar concepts are seen in a new way. The covariance and autocorrelation methods are derived in the time and frequency domains. Both methods are shown to be derivable from a more general concept, that of generalized analysis-by-synthesis, where a nonstationary two-dimensional spectrum is approximated by another model spectrum. Linear prediction analysis is a special case where the model spectrum is all-pole. Also, under the assumption of stationarity the general covariance method reduces to the autocorrelation method.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 31, 1972
Accession Number
AD0749066

Entities

People

  • Jared J. Wolf
  • John I. Makhoul

Organizations

  • BBN Technologies

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Automated Speech Recognition
  • Detection
  • Detectors
  • Dynamic Range
  • Filters
  • Filtration
  • Fourier Series
  • Frequency
  • Frequency Domain
  • Frequency Response
  • Mathematical Filters
  • Numerical Analysis
  • Power Spectra
  • Speech Analysis
  • Stationary Processes
  • Two Dimensional

Readers

  • Speech Processing/Speech Recognition.
  • Statistical inference.