Classification of South African languages using text and acoustic based methods: A case of six selected languages

Peleira Nicholas Zulu

Language variations are generally known to have a severe impact on the performance of Human Language Technology Systems. In order to predict or improve system performance, a thorough investigation into these variations, similarities and dissimilarities, is required. Distance measures have been used in several applications of speech processing to analyze different varying speech attributes. However, not much work has been done on language distance measures, and even less work has been done involving South African languages. This study explores two methods for measuring the linguistic distance of six South African languages. It concerns a text based method, (the Levenshtein Distance), and an acoustic approach using extracted mean pitch values. The Levenshtein distance uses parallel word transcriptions from all six languages with as little as 144 words, whereas the pitch method is text-independent and compares mean language pitch differences. Cluster analysis resulting from the distance matrices from both methods correlates closely with human perceptual distances and existing literature about the six languages.