Bootstrapping a Runyankore CNL from an isiZulu CNL

Proceedings of the 10th International Conference on Natural Language Generation

DeRenzi

2017

Self Cite

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.

Section: Discussionmentioning

confidence: 75%

Section: New Rules and Algorithmsmentioning

confidence: 99%

Section: Cardinality Constraintsmentioning

confidence: 99%

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Evaluation of a Runyankore grammar engine for healthcare messages

Byamugisha

Proceedings of the 10th International Conference on Natural Language Generation

DeRenzi

2017

Self Cite

“…The modularisation method would, theoritically, also be extendable to other related languages in the Nguni group. Moreover, it may also extend to other Bantu langauges outside the Nguni group since Byamugisha, Keet, and DeRenzi (Byamugisha et al, 2016a) have shown that it is possible to bootstrap between geographically distant Bantu languages in knowledge-to-text NLG.…”

Section: Discussionmentioning

confidence: 98%

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

Mahlaza

2019

SACJ

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.

“…Our broader programme of NLG for Bantu languages aims to apply NLG to generate drug explanations in Runyankore-a Bantu language indigenous to Uganda, where English is the official language, but indigenous languages are predominantly spoken in rural areas. Runyankore sentences generated through ontology verbalization (Byamugisha et al, 2016) exposed two crucial issues: (1) What tense and aspect is used in explanations of prescribed medication? and (2) Is a contextfree grammar (CFG) sufficient to conjugate verbs in Runyankore?…”

Section: Introductionmentioning

confidence: 99%

Tense and Aspect in Runyankore Using a Context-Free Grammar

Byamugisha

Proceedings of the 9th International Natural Language Generation Conference

DeRenzi

2016

Self Cite

The provision of personalized patient information has been encouraged as a means of complementing information provided during patient-doctor consultations, and linked to better health outcomes through patient compliance with prescribed treatments. The generation of such texts as a controlled fragment of Runyankore, a Bantu language indigenous to Uganda, requires the appropriate tense and aspect, as well as a method for verb conjugation. We present how an analysis of corpora of explanations of prescribed medications was used to identify the simple present tense and progressive aspect as appropriate for our selected domain. A CFG is defined to conjugate and generate the correct form of the verb.