An assessment of orthographic similarity measures for several African languages

Natural Language Interfaces and tools such as spellcheckers and Web search in one's own language are known to be useful in ICT-mediated communication. Most languages in Southern Africa are under-resourced, however. Therefore, it would be very useful if both the generic and the few language-specific NLP tools could be reused or easily adapted across languages. This depends on the notion, and extent, of similarity between the languages. We assess this from the angle of orthography and corpora. Twelve versions of the Universal Declaration of Human Rights are examined, showing clusters of languages, and which are thus more or less amenable to cross-language adaptation of NLP tools, which do not match with Guthrie zones. To examine the generalisability of these results, we zoom in on isiZulu both quantitatively and qualitatively with four other corpora and texts in different genres. The results show that the UDHR is a typical text document orthographically. The results also provide insight into usability of typical measures such as lexical diversity and genre, and that the same statistic may mean different things in different documents. While NLTK for Python could be used for basic analyses of text, it, and similar NLP tools, will need considerable customization

Evaluation of a Runyankore grammar engine for healthcare messages

Natural Language Generation (NLG) can be used to generate personalized health information, which is especially useful when provided in one's own language. However, the NLG technique widely used in different domains and languages---templates---was shown to be inapplicable to Bantu languages, due to their characteristic agglutinative structure. We present here our use of the grammar engine NLG technique to generate text in Runyankore, a Bantu language indigenous to Uganda. Our grammar engine adds to previous work in this field with new rules for cardinality constraints, prepositions in roles, the passive, and phonological conditioning. We evaluated the generated text with linguists and non-linguists, who regarded most text as grammatically correct and understandable; and over 60\% of them regarded all the text generated by our system to have been authored by a human being

A method for measuring verb similarity for two closely related languages with application to Zulu and Xhosa

There are limited computational resources for Nguni languages and when improving availability for one of the languages, bootstrapping from a related language’s resources may be a cost-saving approach. This requires the ability to quantify similarity between any two closely related languages so as to make informed decisions, of which it is unclear how to measure it. We devised a method for quantifying similarity by adapting four extant similar measures, and present a method of quantifying the ratio of verbs that would need phonological conditioning due to consecutive vowels. The verbs selected are those relevant for weather forecasts for Xhosa and Zulu and newly specified as computational grammar rules. The 52 Xhosa and 49 Zulu rules share 42 rules, supporting informal impressions of their similarity. The morphosyntactic similarity reached 59.5% overall on the adapted Driver-Kroeber metric, with past tense rules only at 99.5%. This similarity score is a result of the variation in terminals mainly for the prefix of the verb