QATIP -- An Optical Character Recognition System for Arabic Heritage Collections in Libraries

Nowadays, commercial optical character recognition (OCR) software achieves very high accuracy on high-quality scans of modern Arabic documents. However, a large fraction of Arabic heritage collections in libraries is usually more challenging - e.g. consisting of typewritten documents, early prints, and historical manuscripts. In this paper, we present our end-user oriented QATIP system for OCR in such documents. The recognition is based on the Kaldi toolkit and sophisticated text image normalization. This paper contains two main contributions: First, we describe the QATIP interface for libraries which consists of both a graphical user interface for adding and monitoring jobs and a web API for automated access. Second, we suggest novel approaches for language modelling and ligature modelling for continuous Arabic OCR. We test our QATIP system on an early print and a historical manuscript and report substantial improvements - e.g. 12.6% character error rate with QATIP compared to 51.8% with the best OCR product in our experimental setup (Tesseract).