casa 17(11): e5

Research Article

Collective Intelligence based Endangered Language Revitalisation Systems: Design, Implementation, and Evaluation

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  • @ARTICLE{10.4108/eai.6-3-2017.152338,
        author={Asfahaan Mirza and David Sundaram},
        title={Collective Intelligence based Endangered Language Revitalisation Systems: Design, Implementation, and Evaluation},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={4},
        number={11},
        publisher={EAI},
        journal_a={CASA},
        year={2017},
        month={3},
        keywords={Collective Intelligence, Language Revitalisation, Endangered Languages, Crowd Sourced, Language Learning, Mobile Apps},
        doi={10.4108/eai.6-3-2017.152338}
    }
    
  • Asfahaan Mirza
    David Sundaram
    Year: 2017
    Collective Intelligence based Endangered Language Revitalisation Systems: Design, Implementation, and Evaluation
    CASA
    EAI
    DOI: 10.4108/eai.6-3-2017.152338
Asfahaan Mirza1,*, David Sundaram1
  • 1: Department of Information Systems and Operations Management, University of Auckland, Auckland, New Zealand
*Contact email: a.mirza@auckland.ac.nz

Abstract

The languages are disappearing at an alarming rate; half of 7105 plus languages spoken today may disappear by end of this century. When a language becomes extinct, communities lose their cultural identity, practices tied to a language and intellectual wealth. The rapid loss of languages motivates this study.
We first introduce collective intelligence, endangered languages, and language revitalisation. Secondly we discuss and explore how to leverage collective intelligence to preserve, curate, discover, learn, share and eventually revitalise endangered languages. Thirdly we compare and synthesise existing language preservation and learning systems. Subsequently, we outline the research methodology. Finally, we propose the design, implementation and evaluation of “Save Lingo” and “Learn Lingo” apps for revitalising endangered languages. The systems are instantiated and validated in context of te reo Māori, Vietnamese and non-roman script languages such as Arabic, Chinese and Hindi.