User-Centric Evaluation of OCR Systems for Kwak'wala

TL;DR

This paper evaluates OCR systems for the endangered Kwak'wala language through a human-centric study, showing OCR significantly reduces manual transcription time and benefits language preservation efforts.

Contribution

It introduces a human-centered evaluation approach for OCR in endangered languages, highlighting practical benefits over traditional error rate metrics.

Findings

OCR reduces manual transcription time by over 50%.

Human-centric evaluation reveals OCR's usefulness beyond error metrics.

Supports language documentation and revitalization efforts.

Abstract

There has been recent interest in improving optical character recognition (OCR) for endangered languages, particularly because a large number of documents and books in these languages are not in machine-readable formats. The performance of OCR systems is typically evaluated using automatic metrics such as character and word error rates. While error rates are useful for the comparison of different models and systems, they do not measure whether and how the transcriptions produced from OCR tools are useful to downstream users. In this paper, we present a human-centric evaluation of OCR systems, focusing on the Kwak'wala language as a case study. With a user study, we show that utilizing OCR reduces the time spent in the manual transcription of culturally valuable documents -- a task that is often undertaken by endangered language community members and researchers -- by over 50%. Our results demonstrate the potential benefits that OCR tools can have on downstream language documentation and revitalization efforts.