Transition Networks for Pattern Recognition.
Abstract
Transition networks along with a discussion of their relationships to grammars of Chomsky's hierarchy is studied. The modified Earley's parsing algorithm for transition network grammars is also presented. A transition network is a model for a grammar. It provides perspicuity in expression and allows efficient parsing algorithms. The stochastic and error correcting versions of transition networks are also presented. The approach of stochastic error correcting transition network analysis is proposed to solve the problem of noise and distortion in syntactic pattern recognition. The advantages of this approach are discussed in detail and illustrated by an experiment on voice-chess language. Finally, an approach to the inference of transition networks is proposed. The inference on the probability assignment over the arcs of stochastic transition networks is also discussed. The inference techniques are illustrated by examples.
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 01, 1975
- Accession Number
- ADA020727
Entities
People
- King Sun Fu
- Su May Chou
Organizations
- Purdue University