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Adapting Nine Traditional Text Readability Measures into Sesotho

This article discusses the adaptation of traditional English readability measures into Sesotho, a Southern African indigenous low-resource language. We employ the use of a translated readability corpus to extract textual features from the Sesotho texts and readability levels from the English translations. We look at the correlation between the different features to ensure that non-competing features are used in the readability metrics. Next, through linear regression analyses, we examine the impact of the text features from the Sesotho texts on the overall readability levels (which are gauged from the English translations). Starting from the structure of the traditional English readability measures, linear regression models identify coefficients and intercepts for the different variables considered in the readability formulas for Sesotho. In the end, we propose ten readability formulas for Sesotho (one more than the initial nine; we provide two formulas based on the structure of the Gunning Fog index). We also introduce intercepts for the Gunning Fog index, the Läsbarhets index and the Readability index (which do not have intercepts in the English variants) in the Sesotho formulas.