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English to Yoruba short message service speech and text translator for android phones

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Abstract

Machine language translation (MLT) has acquired a substantial quantity of investigation consideration in Europe and Asia, but works on African languages, especially the Yoruba language, are rare. There is, however, a communication barrier between the people who solely speak Yoruba and foreign visitors and places where the language is not being said or understood. There is a necessity to focus on the glitches of English to Yoruba machine translations to bridge the communication gap. This study, therefore, implemented the rule-based machine translation technique. The method used involved formulating 20 computational rules for the translation process. Offline Android-based English to Yoruba short message service application was developed using the Android Studio IDE and the some of the available inbuilt android plugins alongside a locally produced bilingual dictionary. This paper also examined translations done by the developed mobile app contrary to human translation to explore why machine translation systems still give faults in interpreting natural human language. A questionnaire was designed for the translations; they were distributed to one hundred individuals. Eighty-one participants gave their feedbacks. The responses were dispensed to statistical examination using SPSS. Discoveries showed that human translation handled best-concerning precision and eloquence, which are knowledgeable by the quality and the quantity of the computational rules formulated.

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Data availability

The datasets used for the study is deposited in the Harvard Dataverse repository. https://doi.org/10.7910/DVN/FPWD3K. Babatunde et al., (2020).

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Authors and Affiliations

  1. Kwara State University, Malete, Kwara State, Nigeria

    Akinbowale Nathaniel Babatunde & Hafsat Omolola Olawuyi

  2. University of Ilorin, Ilorin, Kwara State, Nigeria

    Christiana Oluwakemi Abikoye & Abdulkarim Ayopo Oloyede

  3. Department of Computer Science, Landmark University, Omu Aran, Kwara State, Nigeria

    Roseline Oluwaseun Ogundokun

  4. Summit University, Offa, Kwara State, Nigeria

    Afeez Adeshina Oke

Authors
  1. Akinbowale Nathaniel Babatunde
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  2. Christiana Oluwakemi Abikoye
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  3. Abdulkarim Ayopo Oloyede
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  4. Roseline Oluwaseun Ogundokun
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  5. Afeez Adeshina Oke
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  6. Hafsat Omolola Olawuyi
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Corresponding author

Correspondence to Roseline Oluwaseun Ogundokun.

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No organization has provided financial funding for the study. The authors claimed that they do not have recognized conflicting financial interests or personal relationships that could have affected the research described in this paper.

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Approval to conduct the survey was obtained from the Ethical Committee of Landmark University, Omu Aran, Nigeria and all informed consent were obtained for experimentation with human subjects.

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Babatunde, A.N., Abikoye, C.O., Oloyede, A.A. et al. English to Yoruba short message service speech and text translator for android phones. Int J Speech Technol 24, 979–991 (2021). https://doi.org/10.1007/s10772-021-09852-w

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  • DOI: https://doi.org/10.1007/s10772-021-09852-w

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