A Game-based Approach to Transcribing Images of Text

Abstract

Creating language resources is expensive and time-consuming, and this forms a bottleneck in the development of language technology, for less-studied non-European languages in particular. The recent internet phenomenon of crowd-sourcing offers a cost-effective and potentially fast way of overcoming such language resource acquisition bottlenecks. We present a methodology that takes as its input scanned documents of typed or hand-written text, and produces transcriptions of the text as its output. Instead of using Optical Character Recognition (OCR) technology, the methodology is game-based and produces such transcriptions as a by-product. The approach is intended particularly for languages for which language technology and resources are scarce and reliable OCR technology may not exist. It can be used in place of OCR for transcribing individual documents, or to create corpora of paired images and transcriptions required to train OCR tools. We present Minefield, a prototype implementation of the approach which is currently collecting Arabic transcriptions.

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