THE DIGITISED HOLLE LIST PROJECT: BUILDING A DATABASE FROM LEGACY MATERIALS FOR CONSERVING INDIGENOUS INDONESIAN LANGUAGES
Abstract
Advances in cloud computing, as well as computational tools for extracting text from images, offer an opportunity to scale up the development of digital databases for Indigenous languages. This paper reports on the application of these advances to the digitalisation of old, paper-based lexical items of over a hundred Indigenous languages in Indonesia; these items are part of the so-called Holle List (HL). After introducing the (structure of the) HL, the paper underlines the motivation for the HL digitalisation project. It then provides an overview of Google Colab as a free cloud-computing platform for executing a series of optical character recognition (OCR) operations on hundreds of scanned pages of the HL, utilising pytesseract, a Python interface for Google’s Tesseract-OCR engine. Advantages (e.g., computational searchability and manipulability), as well as issues (especially typos and unrecognised characters) in the plain-text OCR outputs, are discussed. In conclusion, the paper highlights the importance of digital technology in conserving Indigenous languages via digital platforms, despite some unavoidable challenges that require human intervention.
Keywords: Holle List; Indigenous Indonesian languages; Digital Humanities; Lexical databases
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