Feature Selection with Exception Handling - An Example from Phonology

Scheler, Gabriele (1994) Feature Selection with Exception Handling - An Example from Phonology. [Conference Paper]

This is the latest version of this eprint.

Full text available as:

[img] Postscript - Published Version


The goal in this paper is to show how the classification of phonetic features to phonemes can be acquired. This classificational process is modeled by a supervised feature selection method, based on adaptive distance measures. Exception handling is incorporated into a learned distance function by pointwise additions of Boolean functions for individual pattern combinations. An important result is the differentiation of rules and exceptions during learning.

Item Type:Conference Paper
Keywords:phonetic features, distance metrics, outliers, classification
Subjects:Computer Science > Machine Learning
Computer Science > Speech
Computer Science > Statistical Models
Linguistics > Phonology
ID Code:8084
Deposited By: Scheler, Dr Gabriele
Deposited On:09 Nov 2012 19:35
Last Modified:09 Nov 2012 19:35

Available Versions of this Item


Repository Staff Only: item control page