A Comparison of Anapron with Seven other Name-Pronunciation Systems

Abstract

This paper presents an experiment comparing a new name-pronunciation system, Anapron, with seven existing systems: three state-of-the-art commercial systems (from Bellcore Bell Labs, and Dec), two variants of a machine-learning system (NETtalk), and two humans. Anapron works by combining rule-based and case-based reasoning. It is based on the idea that it is much easier to improve a rule-based system by adding case-based reasoning to it than by tuning the rules to deal with every exception. In the experiment described here, Anapron used a set of rules adapted from MITalk and elementary foreign-language textbooks, and a case library of 5000 names. With these components -- which required relatively little knowledge engineering -- Anapron was found to perform almost at the level of the commercial systems, and significantly better than the two versions of NETtalk.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1993
Accession Number
ADA269988

Entities

People

  • Andrew R. Golding
  • Paul Simon Rosenbloom

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Classification
  • Computational Science
  • Computer Science
  • Data Science
  • Databases
  • Engineering
  • Foreign Languages
  • Frequency
  • Frequency Bands
  • Information Science
  • Language
  • Law
  • Linguistics
  • Notation
  • Reasoning
  • Rule Based Systems
  • Test Sets

Fields of Study

  • Computer science

Readers

  • Computer Engineering
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation