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        <title>Evaluation of a Runyankore grammar engine for healthcare messages</title>
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        <namePart type="given">Maria</namePart>
        <namePart type="family">Keet</namePart>
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            <title>Proceedings of the 10th International Conference on Natural Language Generation</title>
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    <abstract>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.</abstract>
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%0 Conference Proceedings
%T Evaluation of a Runyankore grammar engine for healthcare messages
%A Byamugisha, Joan
%A Keet, C. Maria
%A DeRenzi, Brian
%Y Alonso, Jose M.
%Y Bugarín, Alberto
%Y Reiter, Ehud
%S Proceedings of the 10th International Conference on Natural Language Generation
%D 2017
%8 September
%I Association for Computational Linguistics
%C Santiago de Compostela, Spain
%F byamugisha-etal-2017-evaluation
%X 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.
%R 10.18653/v1/W17-3514
%U https://aclanthology.org/W17-3514
%U https://doi.org/10.18653/v1/W17-3514
%P 105-113

Markdown (Informal)

[Evaluation of a Runyankore grammar engine for healthcare messages](https://aclanthology.org/W17-3514) (Byamugisha et al., INLG 2017)

• Evaluation of a Runyankore grammar engine for healthcare messages (Byamugisha et al., INLG 2017)

ACL

• Joan Byamugisha, C. Maria Keet, and Brian DeRenzi. 2017. Evaluation of a Runyankore grammar engine for healthcare messages. In Proceedings of the 10th International Conference on Natural Language Generation, pages 105–113, Santiago de Compostela, Spain. Association for Computational Linguistics.