Long Term Examination of Intra-Session and Inter-Session Speaker Variability

Abstract

Session variability in speaker recognition is a well recognized phenomena, but poorly understood largely due to a dearth of robust longitudinal data. The current study uses a large, long-term speaker database to quantify both speaker variability changes within a conversation and the impact of speaker variability changes over the long term (3 years). Results demonstrate that 1) change in accuracy over the course of a conversation is statistically very robust and 2) that the aging effect over three years is statistically negligible. Finally we demonstrate that voice change during the course of a conversation is, in large part, comparable across sessions.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2009
Accession Number
ADA516541

Entities

People

  • A. D. Lawson
  • A. R. Stauffer
  • B. B. Pokines
  • B. Y. Smolenski
  • E. J. Cupples
  • Matthew K. Leonard

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Acoustic Absorption
  • Air Force
  • Anechoic Chambers
  • Coefficients
  • Computer Science
  • Confidence Limits
  • Databases
  • Decoding
  • Identification
  • Identification Systems
  • Information Science
  • Nonlinear Dynamics
  • Recognition
  • Statistical Analysis
  • Training
  • Urban Areas

Readers

  • Regression Analysis.
  • Speech Processing/Speech Recognition.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference