Clustering of the Least Squares Lattice PARCOR (Partial Correlation) Coefficients: A Pattern-Recognition Approach to Steady State Synthetic Vowel Identification.

Abstract

The partial correlation (PARCOR) coefficients of the least squares lattice filter may be used to conveniently and efficiently represent various types of acoustic signals. Because a stationary time series may be represented by a small number of PARCOR coefficients, the PARCOR coefficients have been widely used as effective pattern recognition parameters for the representation and transmission of information. This thesis establishes the PARCOR coefficients of the least squares lattice filter as efficient and effective pattern recognition features for the classification and identification of synthesized steady state vowel-like sounds. The PARCOR coefficient technique is shown to be a much quicker and more computationally efficient method of vowel identification than densification by formant frequencies, which involves the computations of poles and zeroes and the back-calculation of formant frequencies and format bandwidths. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1983
Accession Number
ADA131503

Entities

People

  • Beth Anne Cooper

Organizations

  • Pennsylvania State University

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Acoustic Signals
  • Acoustics
  • Algorithms
  • Classification
  • Computational Science
  • Computations
  • Filters
  • Filtration
  • Frequency Domain
  • Identification
  • Mathematical Filters
  • Measurement
  • Pattern Recognition
  • Recognition
  • Signal Processing
  • Steady State
  • Time Domain

Fields of Study

  • Engineering

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Microwave Engineering.
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference