Transition Network Grammars for Syntactic Pattern Recognition.

Abstract

The application of transition network grammars to syntactic pattern recognition is studied in this paper. The relation between basic transition networks and context-free grammars is demonstrated. Augmented transition networks can be used to represent context-sensitive, or even type 0 languages. Stochastic transition networks are defined and the parsing of languages represented by transition networks and stochastic transition networks investigated. Error-correcting parsing algorithms are proposed from the viewpoint of syntactic pattern recognition. The voice-chess grammar is used in an experiment to illustrate various parsing results.

Document Details

Document Type
Technical Report
Publication Date
May 15, 1975
Accession Number
ADA015929

Entities

People

  • King Sun Fu
  • S. M. Chou

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computer Graphics
  • Computers
  • Context Free Grammars
  • Formal Languages
  • Grammars
  • Graphics
  • Language
  • Pattern Recognition
  • Recognition
  • Transitions

Fields of Study

  • Engineering

Readers

  • Computational Linguistics
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation
  • AI & ML - Neural Networks