Thesis (MEng)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: We present the development of a pattern recognition system which is capable of classifying
different Spoken Variants (SVs) of South African English (SAE) using a transcriptionless
speech recognition approach. Spoken Variants (SVs) allow us to unify the linguistic
concepts of accent and dialect from a pattern recognition viewpoint. The need for the SAE
SV classification system arose from the multi-linguality requirement for South African
speech recognition applications and the costs involved in developing such applications. / AFRIKAANSE OPSOMMING: Ons beskryf die ontwikkeling van 'n patroon herkenning stelsel wat in staat is om verskillende
Gesproke Variante (GVe) van Suid Afrikaanse Engels (SAE) te klassifiseer met
behulp van 'n transkripsielose spraak herkenning metode. Gesproke Variante (GVe) stel
ons in staat om die taalkundige begrippe van aksent en dialek te verenig vanuit 'n patroon
her kenning oogpunt. Die behoefte aan 'n SAE GV klassifikasie stelsel het ontstaan
uit die meertaligheid vereiste vir Suid Afrikaanse spraak herkenning stelsels en die koste
verbonde aan die ontwikkeling van sodanige stelsels.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/49866 |
| Date | 03 1900 |
| Creators | Du Toit, A. (Andre) |
| Contributors | Du Preez, J. A., Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
| Format | 156 leaves : ill. |
| Rights | Stellenbosch University |
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