A reduced ambiguity lexical system.

Paul Frenger

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PubMed · 15133995

A reduced ambiguity lexical system.

Paul Frenger

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Abstract

Natural human languages have proven to be sub-optimal in artificial intelligence applications because of their tendency to inexact representation of meaning. The author has devised a technique for converting human language to and from a compact byte-coded intermediate representation, which is processed more easily by computer systems. A specialized lexical engine based on IEEE Standard 1275-1994 was created to embed redundant information invisibly within the byte-coded text stream, to enable use of a variety of alphabets, grammars, and pronunciation rules (including slang and regional dialects). Very large vocabularies in a variety of human languages are supported. These lexical tools are designed to facilitate speech recognition and speech synthesis subsystems, universal translators and machine intelligence systems.

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Algorithms Database Management Systems Dictionaries as Topic Information Storage and Retrieval Language Natural Language Processing Software Terminology as Topic Evaluation Study Journal Article

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Paul Frenger. 2004. A reduced ambiguity lexical system.. https://pubmed.ncbi.nlm.nih.gov/15133995/

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