Diacritic-aware Yorùbá spell checker

• Autorzy: Asahiah Franklin Oládiípò , Onífádé Mary Taiwo , Asahiah Adekemisola Olufunmilayo , Adegunlehin Abayomi Emmanuel , Amoo Adekemi Olawunmi

Identyfikatory

DOI

10.7494/csci.2023.24.1.4494

• Języki publikacji: EN

Abstrakty

EN

Spell checking and correction is still in its infancy for the Yorùbá language; existing tools cannot be directly applied to address the problem, as Yorùbá uses diacritics extensively for distinguishing phonemes and for marking tone. A model was formulated as a parallel combination of a unigram language model and a diacritic model to form a dictionary sub-model that can be used by error-detection and candidate-generation modules. The candidate-generation module was implemented as a reverse Levensthein edit-distance algorithm. The system was evaluated by using detection accuracy (calculated from the precision and recall) and suggestion accuracy (SA) as metrics. Our experimental setups compared the performance of the component subsystems when used alone and with their combination into a unified model. The detection accuracies for the different models range from 93.23 to 95.01%, and the suggestion accuracies range from 26.94 to 72.10%. The results indicated that each of the sub-models in the dictionary played different roles.

Słowa kluczowe

EN

tone; phonemes; diacritic; unigram; tools

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2023
• Tom: T. 24 (1)
• Strony: 31--51
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Asahiah Franklin Oládiípò

• Obafemi Awolowo University, Ile-Ife, Nigeria

autor

Onífádé Mary Taiwo

• Kings University, Gbongan-Osogbo Road, Ode-Omu, Nigeria
• Obafemi Awolowo University, Ile-Ife, Nigeria

autor

Asahiah Adekemisola Olufunmilayo

• Obafemi Awolowo University, Ile-Ife, Nigeria

autor

Adegunlehin Abayomi Emmanuel

• Obafemi Awolowo University, Ile-Ife, Nigeria

autor

Amoo Adekemi Olawunmi

• Obafemi Awolowo University, Ile-Ife, Nigeria

Bibliografia

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).