Speech-to-Text Hybrid English to Yoruba SMS Translator

  • Akinbowale Nathaniel Babatunde Kwara State University, Malete, Kwara State, Nigeria
  • Ronke Seyi Babatunde Kwara State University, Malete, Kwara State, Nigeria
  • Bukola Fatimah Balogun Kwara State University, Malete, Kwara State, Nigeria
  • Emmanuel Umar Tai Solarin University of Education, Ogun state
  • Shuaib Babatunde Mohammed Kwara State University, Malete, Kwara State, Nigeria
  • Afeez Adeshina Oke Federal College of Education, Iwo, Osun State
  • Kolawole Yusuf Obiwusi Summit University, Offa, Kwara State, Nigeria
Keywords: Google translator, machine translation, natural language processing, speech synthesizer, translation, Yoruba language

Abstract

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The necessity for quick translation from English to regional languages, such as Yoruba language arises from the fact that it is imperative for the widespread dissemination of knowledge and information. A speech-to-text enabled translation on Android devices and text-to-speech synthesizer (TTS) capable to deliver real-time translation of Yoruba language is presented. It increases the naturalness of oral communications, eases the communication, and furthers the understanding and use of Yoruba language among people of different backgrounds. This speech-to-text enabled translation system uses NLP on one hand and a TTS interpretation technique on the other. It uses an Android Google translation API synthesizer and a recognizer for English and Yoruba translation. The current study attempted to develop an English to Yoruba SMS translator with built-in text-to-speech and speech-to-text features. The Android Studio Integrated Development Environment was used to create the system (IDE). Whereas, a statistical machine translation algorithm was adopted for the implementation of Google API translation for English speech to text, TTS conversions, and Yoruba translations. About 100 computational rules were formulated for the Yoruba voice translation process. For the translation processes, a questionnaire was also created and circulated to 350 people. Approximately, 96% of those who responded provided input. The responses were subjected to SPSS statistical analysis. The results suggested that the translation system has a 92% accuracy which is comparable to that of a human (expert).

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References

P. Hacker, Insight and illusion: Themes in the Philosophy of Wittgenstein. Anthem Press, 2021.

M. Foucault, Language, Counter-Memory, Practice. Cornell University Press, 2021.

A. M. Guerrettaz, M. M. Engman, and Y. Matsumoto, “Empirically defining language learning and teaching materials in use through socio-material perspectives”, Mod. Lang. J., vol. 105, no. S1, pp. 3–20, Jan. 2021, doi: https://doi.org/10.1111/modl.12691

A. MacLaughlin, J. Wihbey, A. Bajak, and D. A. Smith, “Source attribution: Recovering the press releases behind health science news”, In Proc. Int. AAAI Conf. Web Social Med., May 2020, pp. 428–439.

F. De-Varennes, Language, minorities, and human rights. Brill, 2021.

L. K. Ajayi, A. Azeta, S. Misra, I. Odun-Ayo, P. T. Ajayi, V. Azeta, and A. Agrawal, “Enhancing the low adoption rate of m-commerce in Nigeria through Yorùbá voice technology” presented at the International Conference on Hybrid Intelligent Systems, Dec. 14–16, 2020.

T. Balogun, “An endangered Nigerian indigenous language: The case of Yoruba language”, Afr. Nebula, no. 6, pp. 70–82, 2013.

F. O. Olaide, A. B. Kayode, A. O. Sunday, and A. A. Olusola, “Android platform for machine translation-a focus on Yorùbá language” Am. J. Comput. Commun. Cont., vol. 5, no. 1, pp. 16–23, 2018.

R. G. Jimoh, and A. N. Babatunde, “Enhanced automated teller machine using short message service authentication verification”, Afr. J. Comput. ICTs, vol. 7, no. 1, pp. 115–120, 2014.

R. S. Babatunde, A. N. Babatunde, B. F. Balogun, E. Umar, A. A. Oke, and K. Y. Obiwusi, “A predictive system for Parkinson disease using Generative Adversarial network (GAN). FUW Trends Sci. Technol. J., vol. 8, no. 3, pp. 381–390, 2023.

D. Adelani, D. Ruiter, J. Alabi, D. Adebonojo, A. Ayeni, M. Adeyemi, and C. Espana-Bonet, “The effect of domain and diacritics in Yorùbá-English neural machine translation”, arxiv, Art. no. 2103.08647, 2021, doi: https://doi.org/10.48550/arXiv.2103.08647

S. Eludiora and B. Ajibade, “Design and implementation of English to Yoruba verb phrase machine translation system”, arxiv, Art. no. 2104.04125, 2023, doi: https://doi.org/10.48550/arXiv.2104.04125

F. Fatoye, C. E. Mbada, T. O, Oladayo, O. A. Idowu, O. O. Oyewole, C. Fatoye, and K. I. Oke, “Validation of the Yoruba version of the pain self-efficacy questionnaire in patients with chronic low back pain”, Spine, vol. 46, no. 9, E528–E533, May 2021, doi: https://doi.org/10.1097/BRS.0000000000003870

A. N. Babatunde, C. O. Abikoye, A. A., Oloyede, R. O. Ogundokun, A. A. Oke, and H. O. Olawuyi, “English to Yoruba short message service speech and text translator for android phones” Int. J. Speech Technol., vol. 24, no. 4, pp. 979–991, May 2021, doi: https://doi.org/10.1007/s10772-021-09852-w

R. S. Babatunde, A. N. Babatunde, B. F. Balogun, I. A. Yakubu, R. O. Ogundokun, K. Y. Obiwusi and E. Umar, “A comparison of Boosting techniques for Classification of Microarray data”, Ilorin J. Comput. Sci. Info. Technol., vol. 6, no. 2, pp.1–8, Feb. 2023.

A. Kalyani and P.S. Sajja, “A review of machine translation systems in India and different translation evaluation methodologies” Int. J. Comput. Appl., vol. 121, no. 23, July 2015.

T. Van-Leeuwen, H. Moed, R. Tijssen, M. Visser, and A. Van-Raan, “Language biases in the coverage of the Science Citation Index and its consequences: International comparisons of national research performance”, Scientometrics, vol. 51, no. 1, 335–346, Apr. 2021, doi: https://doi.org/10.1023/A:1010549719484

R. O. Ogundokun, J. B. Awotunde, S. Misra, E. A. Adeniyi, and V. Jaglan, V. “An android based language translator application”, J. Phy., vol. 1767, no. 1, Art. no. 012032, 2021.

W. Harcourt, “Translocalities/ Translocalidades: Feminist politics of translation in the Latin/a Américas”, Hisp. Am. Hist. Rev., vol. 96, no. 3, pp. 603–605, 2016, doi: https://doi.org/10.1215/00182168-3601622

K. Angelov, B. Bringert, and A. Ranta, “Speech-enabled hybrid multilingual translation for mobile devices”, In Proc. Demonst. 14th Conf. Eur. Chap. Assoc. Comput. Linguist., April, 2014, pp. 41–44.

A. Grace, N. Kemp, F. H. Martin, and R. Parrila, “Undergraduates' use of text messaging language: Effects of country and collection method”, Writing Syst. Res., vol. 4, no. 2, pp. 167–184, Aug. 2012, doi: https://doi.org/10.1080/17586801.2012.712875

S. Dubey, “Survey of machine translation techniques”, Int. J. Adv. Res. Comput. Sci. Manag. Stud. Spec. Issue, vol. 5, no. 2, pp. 39–51, Feb. 2017.

S. I. Eludiora and O. A. Odetunji, “Development of an English to Yoruba machine translator” Int. J. Mod. Edu. Comput. Sci., vol. 3, no. 11, pp. 8–19, 2016, doi: https://doi.org/10.5815/ijmecs.2016.11.02

A. O. Agbeyangi, S. I. Eludiora, and D. I. Adenekan, “English to Yorùbá machine translation system using a rule-based approach”, J. Multidiscip. Eng. Sci. Technol., vol. 2, no. 8, pp. 2275–2280, Aug. 2015.

A. Kalyani, H. Kumud, S. P. Singh, A. Kumar, and H. Darbari, “Evaluation and ranking of machine-translated output in Hindi language using precision and recall-oriented metrics”, arxiv, Art. no. 1404.1847, 2014, doi: https://doi.org/10.48550/arXiv.1404.1847

D. D. Rao, “Machine translation: A gentle introduction”, Resonance, vol. 3, no. 7, pp. 61–70, July 1998, doi: https://doi.org/10.1007/BF02837314

S. Mehmet and D. Duman, "Multilingual chat through machine translation: A case of English-Russian," Meta, vol. 58, no. 2, p. 397–410, Aug. 2013, https://doi.org/10.7202/1024180ar

K. W. Church and E. H. Hovy, “Good applications for crummy machine translation”, Mach. Translat., vol. 8, no. 4, pp. 239–258, Dec. 1993, doi: https://doi.org/10.1007/BF00981759

C. Ofulue, “Interconnectivity in other tongues: A sociolinguistic study of SMS text messages in Yoruba”, Issues Intercul. Commun., vol. 1, no. 2, pp. 189–200, 2008.

O. I., Akinwale, A. O. Adetunmbi, O. O. Obe, and A. T. Adesuyi, “Web-based English to Yoruba machine translation”, Int. J. Lang. Lingu., vol. 3, no. 3, pp. 154–159, May 2015, doi: https://doi.org/10.11648/j.ijll.20150303.17

O. O. Fagbolu, B. K., Alese, and S. O. Adewale, “Development of a digital Yorùbá Phrasebook on a mobile platform”, in Proc. Nigerian Comput. Soc. (NCS) 25th Ann. Conf., April, 2014, pp. 13–19.

N. A. Omoregbe, A. A. Azeta, A. O. Adewumi, and O. O. Omotoso, “Design and implementation of a Yoruba language mobile tutor”, in Proc. EDULEARN14 Conf., 2014, pp. 3942–3947.

M. S. Yahaya, O. E. Stella, I. Anda, and A. Mamman, “Agricultural e-extension services: a hybrid of multilingual translation text-to-speech-a framework”, I-manager’s J. Pattern Recog., vol. 5, No. 3, Mar. 2019, doi: https://doi.org/10.26634/jpr.5.3.15679

C. C. Evelyn, E. O. Bennett, and O. E. Taylor, “A natural language processing system for english to igbo language translation in android”, Int. J. Comput. Sci. Math. Theo., vol. 5, no. 1, pp. 64–75, 2019.

A. A. Age, O. O. Oyeyemi, A. Q. Afolabi, C. Okoh, O. S. Gbala, and I. O. Ajayi, “English-Yoruba translator with speech to text recognition”, Undergraduate Project, Dept. Comput. Sci., Kwara State University, Malete, Kwara State Nigeria, 2020.

M. T. Singh, R. Borgohain, and S. Gohain, “An English-Assamese machine translation system”, Int. J. Comput. Appl., vol. 93, no. 4, pp. 1–6, May 2014.

G. Korotenko and L. Korotenko, “Paradigms of programming languages and the difficulty of organizing the algorithms and data structures course”, Technium, vol. 3, no. 4, pp. 25–37, 2021.

L. F. Cortés-Coy, M. Linares-Vásquez, J. Aponte, and D. Poshyvanyk, “On automatically generating commit messages via summarization of source code changes”, presented at the IEEE 14th International Working Conference on Source Code Analysis and Manipulation, Victoria, BC, Canada, Sept. 28–29, 2014.

A. N. Babatunde, A. A. Oke, B. F. Balogun, T. A. AbdulRahman, and R. O. Ogundokun, “A deep neural network-based yoruba intelligent chatbot system”, J. Digit. Innov. Contemp. Res. Sci. Eng. Technol., vol. 10, no. 2, pp 69–80, 2022, doi: https://doi.org/10.22624/AIMS/DIGITAL/V10N2P4

R. Taiwo, “The thumb tribe: Creativity and social change through SMS in Nigeria”, Calif. Linguist. Notes, vol. 35, no 1, pp. 1–18, 2010.

Published
2024-06-19
How to Cite
Babatunde, A. N., Babatunde, R. S., Balogun, B. F., Umar, E., Mohammed, S. B., Oke, A. A., & Obiwusi, K. Y. (2024). Speech-to-Text Hybrid English to Yoruba SMS Translator . Innovative Computing Review, 4(1), 15-36. https://doi.org/10.32350/icr.41.02
Section
Articles