Speaker Identification Using the Two-Dimensional Cepstrum Transform.

Abstract

This thesis investigates the application of the two-dimensional cepstrum transform to a speaker identification System. Two distance measures are implemented for identification decision; the Euclidean distance and a weighted two-dimensional cepstral distance. The study considers three words to be tested under several noise levels. The effect of speaking rate during recordings is examined and is shown to be critical. Results show identification rates in the range of 95% to 98.5% for 50 dB signal to noise ratio and 57.65% to 80.7% for 0 dB signal to noise ratio.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1995
Accession Number
ADA294204

Entities

People

  • Ioannis Lelakis

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Automated Speech Recognition
  • Biometric Security
  • Electrical Engineering
  • Engineering
  • Frequency
  • Identification
  • Identification Systems
  • Language
  • Larynx
  • New York
  • Noise
  • Nose
  • Recognition
  • Security
  • Signal Processing
  • Time Domain
  • Two Dimensional

Readers

  • Graph Algorithms and Convex Optimization.
  • Speech Processing/Speech Recognition.