EAI Endorsed Transactions on Context-aware Systems and Applications (Mar 2017)

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

  • Asfahaan Mirza,
  • David Sundaram

DOI
https://doi.org/10.4108/eai.6-3-2017.152338
Journal volume & issue
Vol. 4, no. 11
pp. 1 – 11

Abstract

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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.

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