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Proceedings Paper

Natural language understanding and speech recognition for industrial vision systems
Author(s): Bruce G. Batchelor
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Paper Abstract

The accepted method of programming machine vision systems for a new application is to incorporate sub-routines from a standard library into code, written specially for the given task. Typical programming languages that might be used here are Pascal, C, and assembly code, although other `conventional' (i.e., imperative) languages are often used instead. The representation of an algorithm to recognize a certain object, in the form of, say, a C language program is clumsy and unnatural, compared to the alternative process of describing the object itself and leaving the software to search for it. The latter method, known as declarative programming, is used extensively both when programming in Prolog and when people talk to one another in English, or other natural languages. Programs to understand a limited sub-set of a natural language can also be written conveniently in Prolog. The article considers the prospects for talking to an image processing system, using only slightly constrained English. Moderately priced speech recognition devices, which interface to a standard desk-top computer and provide a limited repertoire (200 words) as well as the ability to identify isolated words, are already available commercially. At the moment, the goal of talking in English to a computer is incompletely fulfilled. Yet, sufficient progress has been made to encourage greater effort in this direction.

Paper Details

Date Published: 1 November 1992
PDF: 12 pages
Proc. SPIE 1823, Machine Vision Applications, Architectures, and Systems Integration, (1 November 1992); doi: 10.1117/12.132075
Show Author Affiliations
Bruce G. Batchelor, Univ. of Wales College Cardiff (United Kingdom)

Published in SPIE Proceedings Vol. 1823:
Machine Vision Applications, Architectures, and Systems Integration
Bruce G. Batchelor; Susan Snell Solomon; Frederick M. Waltz, Editor(s)

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