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Architecting Crowd-Sourced Language Revitalisation Systems: Generalisation and Evaluation to Te Reo Māori and Vietnamese

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Book cover Computational Social Networks (CSoNet 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9795))

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Abstract

Many linguists claim as many as half of the world’s nearly 7,105 languages spoken today could disappear by the end of this century. When a language becomes extinct, communities lose their cultural identity and practices tied to a language, and intellectual wealth. Preservation of endangered languages is a critical but challenging effort. A language is not preserved and revitalized by just documenting, archiving and developing shared resources. The revitalisation is highly dependent on the learning and usage of the language. Most current systems and approaches do one or the other. There are few systems or approaches that interweave preservation with learning. The purpose of our research is to architect a language revitalisation system that (a) leverages and integrates crowd-sourced collective intelligence approaches with knowledge management approaches to (b) capture, curate, discover, and learn endangered languages. We propose and implement an generalisable architecture that can support any language revitalisation effort in terms of capture, curate, discover, and learn. The validity of the research was tested by implementing the system to support Te Reo Maori and Vietnamese. Furthermore, we evaluate the concepts, processes, architecture, and implementation using a number of mechanisms.

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Authors and Affiliations

  1. Department of Information Systems and Operations Management, University of Auckland, Auckland, New Zealand

    Asfahaan Mirza & David Sundaram

Authors
  1. Asfahaan Mirza
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  2. David Sundaram
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Correspondence to Asfahaan Mirza .

Editor information

Editors and Affiliations

  1. Ton Duc Thang University , Ho Chi Minh City, Vietnam

    Hien T. Nguyen

  2. VSB-Technical University of Ostrava , Ostrava, Poland

    Vaclav Snasel

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Mirza, A., Sundaram, D. (2016). Architecting Crowd-Sourced Language Revitalisation Systems: Generalisation and Evaluation to Te Reo Māori and Vietnamese. In: Nguyen, H., Snasel, V. (eds) Computational Social Networks. CSoNet 2016. Lecture Notes in Computer Science(), vol 9795. Springer, Cham. https://doi.org/10.1007/978-3-319-42345-6_29

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  • DOI: https://doi.org/10.1007/978-3-319-42345-6_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42344-9

  • Online ISBN: 978-3-319-42345-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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