On Syntactic Pattern Recognition and Stochastic Languages.

Abstract

Some preliminary thoughts regarding the potential applications of stochastic languages to syntactic pattern recognition are discussed in this paper. Emphasis is on the description of noisy and/or distorted patterns and the learning of grammar (structural description) from the actual pattern samples. It is demonstrated by several very simple examples and sometimes with rather heuristic justifications that the use of probability information in syntactic pattern recognition would make the syntactic approach more flexible and attractive. It is expected that the use of probability information in syntactic analysis (recognition), though not discussed in this paper, would probably improve the efficiency and flexibility of the analysis procedure. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1971
Accession Number
AD0726625

Entities

People

  • King Sun Fu

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Efficiency
  • Grammars
  • Identification
  • Language
  • Learning
  • Linguistics
  • Pattern Recognition
  • Probability
  • Recognition
  • Resilience

Readers

  • Artificial Intelligence
  • Speech Processing/Speech Recognition.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Machine Translation