IJIET 2020 Vol.10(8): 590-596 ISSN: 2010-3689
doi: 10.18178/ijiet.2020.10.8.1429

Helping People with Language Learning Disabilities Using Native Mobile Voice Recognition — Exploring Its Limits and Advantages

C. Alonso, T. Read, and J. J. Astrain

Abstract—This article presents an intelligent system for people with language learning disabilities called MarLuc. MarLuc aims to improve people’s skills in their native language rather than a second language. The system was born as a tiny Computer Assisted Language Learning (CALL) web-based application targeted to improve pronunciation. Later it became a Mobile Assisted Language Learning (MALL) application and has therefore incorporated some powerful native resources such as voice recognition present on mobile devices. Working with personal mobile devices has brought new exciting possibilities, including but not limited to easy access to native voice recognition and the utilization of bots. In this study, we will show the advantages and some limitations of using native Siri or Android based voice recognition.

Index Terms—MarLuc, computer assisted language learning, mobile assisted language learning, language learning disabilities, hybrid mobile applications.

C. Alonso and J. J. Astrain are with the Department of Statistics, Computer Science and Mathematics, Public University of Navarre (UPNA), 31006 Pamplona, Spain (e-mail: losalo@unavarra.es, josej.astrain@unavarra.es). T. Read is with the Department of Languages and Computer Systems, National University of Distance Education (UNED), 28040 Madrid, Spain (e-mail: tread@lsi.uned.es).

[PDF]

Cite:C. Alonso, T. Read, and J. J. Astrain, "Helping People with Language Learning Disabilities Using Native Mobile Voice Recognition — Exploring Its Limits and Advantages," International Journal of Information and Education Technology vol. 10, no. 8, pp. 590-596, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (Since 2019), INSPEC (IET), EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net