Determination of Optimal Training Methodologies for Discrete/Dependent Speech Recognition (SR) Systems

Abstract

A research experiment was conducted to determine whether various combinations of training methodologies and speaking voices would affect recognition accuracies amongst unique speaker dependent speech recognition (SR) systems. The experiment used a SR system (VOTAN VTR 6050II) which is based on VOTAN (proprietary) technology. Ten subjects trained five different voice patterns each and conducted four natural voice tests to compile statistics about the recognition accuracy for each pattern. Two patterns (natural voice and declarative voice) were retested using a declarative voice. The experiment was successful and demonstrated that different combinations of training methodologies and speaking voices can significantly affect the performance of (unique discrete/dependent SR systems. This thesis discusses the research methodology, reviews and analyzes the data collected, and states conclusions drawn about the particular dependent SR system used in the experiment.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1992
Accession Number
ADA247490

Entities

People

  • Mark C. Rhoads

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Analysis Of Variance
  • Automated Speech Recognition
  • California
  • Computers
  • Data Science
  • Errors
  • Identification
  • Information Science
  • Recognition
  • Speech
  • Statistics
  • Technical Information Centers
  • Template Patterns
  • Training
  • Word Recognition

Readers

  • Aviation Science / Aeronautics.
  • Computational Linguistics
  • Software Engineering.

Technology Areas

  • AI & ML