Browsing by Author "Olani, Gaddisa"

Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Design and Implementation of Afaan Oromo Spell Checker
    (Addis Ababa, Ethiopia, 2013-06) Olani, Gaddisa; Midekso, Dida (PhD)
    Developing language applications or localization of software ;s a resource intensive task Ihal requires the active participation of stakeholders with various backgrounds (i.e. from lingllislic and campl/llI/iollal perspecli\'e~~. With a cons/ani increase in /he amou1Ifs of electronic information and the diverJ'ily of languages which are used to produce them, these challenges get compounded. Various researches ;n the fields of computotionollinguis/ics and computer science have been carried oul while slill many more are on Iheir way 10 alleviate such problems. Spell checker is one pOlential candidate 10 this. Use 0/ compUlers for document preparation is one of those many ,asks undertaken by different organizations. Introducing texts /0 word processing tools may result in spelling errors. Hence, texl processing applica/ion software has !>pell checkers. Inlegraling spell checker in/o word processors reduces Ihe amount of time alld energy lpentto find and correct/he misl-peJ/ed lYord. However, these lools are not ami/able for A/aan Oromo language, Lowland East Cushitic sub-family of the Afro-asialic s/lper·phylum language family spoken in Ethiopia. In this thesis, we describe the design aml implementation 0/ AfaWl Oromo spell checker. Morphology ba~ed (i.e. dictionary look-up with morphological rule!>) computational model was employed to design and develop Afaan Oromo Spell Checker (AOSq. Algorithms Ihat take Ihe morphological properties of Afaan Oromo into consideration are developed/rom scratch and applied, as there are no previous such allemplS. The proposed system was evaluated using Iwo datasets 0/ different size. The experiment result shows thai the lexicon size and nIles in the knowledge base play a vital role to recognize the valid input word, flag Ihe invalid word and generate correct suggestion/or Ihe misspelled word. In general, the algorilhms and techniques used in this study oblained good performance when compared to the other resource-rich languages like English The resalt obtained encourages the IIndertaking of further research in the area, especially wil the aim of developing a full-fledged Afaan Oromo spell checker.
  • No Thumbnail Available
    Item
    Design and Implementation of Afaan Oromo Spell Checker
    (Addis Ababa, Ethiopia, 2013-06) Olani, Gaddisa; Midekso, Dida (PhD)
    Developing language applications or localization of software ;s a resource intensive task Ihal requires the active participation of stakeholders with various backgrounds (i.e. from lingllislic and campl/llI/iollal perspecli\'e~~. With a cons/ani increase in /he amou1Ifs of electronic information and the diverJ'ily of languages which are used to produce them, these challenges get compounded. Various researches ;n the fields of computotionollinguis/ics and computer science have been carried oul while slill many more are on Iheir way 10 alleviate such problems. Spell checker is one pOlential candidate 10 this. Use 0/ compUlers for document preparation is one of those many ,asks undertaken by different organizations. Introducing texts /0 word processing tools may result in spelling errors. Hence, texl processing applica/ion software has !>pell checkers. Inlegraling spell checker in/o word processors reduces Ihe amount of time alld energy lpentto find and correct/he misl-peJ/ed lYord. However, these lools are not ami/able for A/aan Oromo language, Lowland East Cushitic sub-family of the Afro-asialic s/lper·phylum language family spoken in Ethiopia. In this thesis, we describe the design aml implementation 0/ AfaWl Oromo spell checker. Morphology ba~ed (i.e. dictionary look-up with morphological rule!>) computational model was employed to design and develop Afaan Oromo Spell Checker (AOSq. Algorithms Ihat take Ihe morphological properties of Afaan Oromo into consideration are developed/rom scratch and applied, as there are no previous such allemplS. The proposed system was evaluated using Iwo datasets 0/ different size. The experiment result shows thai the lexicon size and nIles in the knowledge base play a vital role to recognize the valid input word, flag Ihe invalid word and generate correct suggestion/or Ihe misspelled word. In general, the algorilhms and techniques used in this study oblained good performance when compared to the other resource-rich languages like English The resalt obtained encourages the IIndertaking of further research in the area, especially wil the aim of developing a full-fledged Afaan Oromo spell checker.