Helping people with language learning disabilities using native mobile voice recognition: exploring its limits and advantages
Fecha
2020Versión
Acceso abierto / Sarbide irekia
Tipo
Artículo / Artikulua
Versión
Versión publicada / Argitaratu den bertsioa
Impacto
|
10.18178/ijiet.2020.10.8.1429
Resumen
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) applicati ...
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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. [--]
Materias
MarLuc,
Computer assisted language learning,
Mobile assisted language learning,
Language learning disabilities,
Hybrid mobile applications
Editor
International Journal of Information and Education Technology
Publicado en
International Journal of Information and Education Technology, 2020, 10(8), 590-596
Departamento
Universidad Pública de Navarra. Departamento de Estadística, Informática y Matemáticas /
Nafarroako Unibertsitate Publikoa. Estatistika, Informatika eta Matematika Saila
Versión del editor
Entidades Financiadoras
This work was supported in part by the Government of Navarre (Spain) under research Grant 0011-1365-2018-000157 (TuSpeaking).