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International Conference on Information and Communication Technology for Development for Africa

ICT4DA 2019: Information and Communication Technology for Development for Africa pp 341–358Cite as

Design and Development of Sentence Parser for Afan Oromo Language

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1026))

Abstract

Parser is an efficient and accurate enough to be useful in many natural language processing systems, most notably in machine translation [1]. Previously many sentence parsers are developed for foreign languages such as English, Arabic, etc. as well as for Amharic language from local languages of Ethiopia. However, to the best of the researcher’s knowledge concerned, there is no Afan Oromo sentence parser for simple and complex sentences. Thus, we proposed to develop a sentence parser for Afan Oromo language. Parsing Afan Oromo sentence is needed and a necessary mechanism for other natural language processing applications like machine translation, question answering, knowledge extraction and information retrieval, particularly for Afan Oromo language. Rule-based parser using a top-down chart parsing algorithm for Afan Oromo sentences presented in this paper. Context Free Grammar (CFG) is used to represent the grammar. 500 sentences were prepared for sample corpus and CFG rules are extracted manually from sample tagged corpus. We also developed simple algorithm of a lexicon generator to automatically generate the lexical rules. Python programming language and NLTK are used as an implementation tools for this study. From the total of sample dataset 70% is simple sentence type because of we considered four different types of simple sentences (declaratives, interrogatives, imperatives and exclamatory sentences) and the rest 30% is complex sentence type. The parser was trained on 400 sentences of training dataset with the accuracy of 98.25% and tested on 100 sentences of testing dataset with the accuracy of 91%. The experimental results on a parser is an encouraging result since it is the first work for simple and complex sentences of Afan Oromo language.

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Author information

Authors and Affiliations

  1. ICT for Development (ICT4D) Research Center, Bahir Dar Institute of Technology, Bahir Dar University, P.O. Box. 26, Bahir Dar, Ethiopia

    Hailu Beshada Balcha & Tesfa Tegegne

  2. Faculty of Computing, Bahir Dar Institute of Technology, Bahir Dar University, P.O. Box. 26, Bahir Dar, Ethiopia

    Hailu Beshada Balcha & Tesfa Tegegne

Authors
  1. Hailu Beshada Balcha
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  2. Tesfa Tegegne
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Corresponding authors

Correspondence to Hailu Beshada Balcha or Tesfa Tegegne .

Editor information

Editors and Affiliations

  1. Council for Scientific and Industrial Research, Meraka ICT Institute, Pretoria, South Africa

    Fisseha Mekuria

  2. Department of Future Technologies, University of Turku, Turku, Finland

    Ethiopia Nigussie

  3. ICT4D Research Center, Bahir Dar University, Bahir Dar , Ethiopia

    Tesfa Tegegne

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Balcha, H.B., Tegegne, T. (2019). Design and Development of Sentence Parser for Afan Oromo Language. In: Mekuria, F., Nigussie, E., Tegegne, T. (eds) Information and Communication Technology for Development for Africa. ICT4DA 2019. Communications in Computer and Information Science, vol 1026. Springer, Cham. https://doi.org/10.1007/978-3-030-26630-1_29

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  • DOI: https://doi.org/10.1007/978-3-030-26630-1_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-26629-5

  • Online ISBN: 978-3-030-26630-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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