Original Research

Neural networks as possible hyphenation technique for Afrikaans

Machteld Fick
Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie | Vol 22, No 1 | a203 | DOI: https://doi.org/10.4102/satnt.v22i1.203 | © 2003 Machteld Fick | This work is licensed under CC Attribution 4.0
Submitted: 26 September 2003 | Published: 26 September 2003

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Machteld Fick, Departement Kwantitatiewe Bestuur, Universiteit van Suid-Afrika, South Africa

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Abstract

In Afrikaans compound words are written as one word. New words are therefore created by simply joining words. Word hyphenation during typesetting by computer is often a problem, because the source of reference changes all the time. A neural network (feedforward backpropagation) was trained with about 5 000 Afrikaans words with correct syllabification. The neural network classified 97,56% of possible points in 5 000 randomly chosen words correctly as either valid or invalid hyphenation points. In a test with 510 words from an Afrikaans magazine the neural network classified 98,75% of possible positions correctly. We came to the conclusion that neural networks can be used successfully as hyphenation technique for Afrikaans.


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