Development of a spoken language identification system for South African languages

Abstract

This article introduces the first Spoken Language Identification system developed to distinguish among all eleven of South Africa’s official languages. The PPR-LM (Parallel Phoneme Recognition followed by Language Modeling) architecture is implemented, and techniques such as phoneme frequency filtering, which aims to utilize the available training data to maximum efficiency, are utilized. The system performs reasonably well, achieving an overall accuracy of 71.72% on test samples of three to ten seconds in length. This accuracy improves when the predicted results are combined into language families, reaching an overall accuracy of 82.39%.