Abstract of FKI-178-93

Document-Name:  fki-178-93.ps.gz
Title:          Feature Selection with Exception Handling Using
                Adaptive Distance Measures- An example from phonetics
Authors:	Gabriele Scheler 
Revision-Date:	1993/27/07 
Category:	Technical Report (Forschungsberichte Künstliche Intelligenz)
Abstract:	The goal in this paper is to show how the classification of 
                patterns of phonetic features (=phones) to phonemes can be 
                acquired. This classificational process is modelled by a 
                supervised feature selection method, based on a weighted 
                Hamming distance, augmented by Boolean functions describing 
                exceptions. An important aspect is the differentiation of 
                rules and exceptions during learning.
Keywords:	feature selection, phonology, language acquisition,
		distance functions, Boolean function learning,
		learning from examples
Size:		9 pages
Language:	English
ISSN:		0941-6358
Copyright:	The ``Forschungsberichte Künstliche Intelligenz''
		series includes primarily preliminary publications,
		specialized partial results, and supplementary
		material. In the interest of a subsequent final
		publication these reports should not be copied. All
		rights and the responsability for the contents of the
		report are with the authors, which would appreciate
		critical comments.

Gerhard Weiss