An Interactive Approach with Off-Line and On-Line Handwritten Text Recognition Combination for Transcribing Historical Documents

Abstract

Automatic transcription of historical documents is becoming an important research topic, specially because of the increasing number of digitised historical documents that libraries and archives are publishing. However, state-of-the-art handwritten text recognition systems are far from being perfect. Therefore, to have perfect transcriptions, human expert revision is required to really produce a transcription of standard quality. In this context, an interactive assistive scenario, where the automatic system and the human transcriber cooperate to generate the perfect transcription, would allow for a more effective approach. In this paper we present a multimodal interactive transcription system where user feedback is provided by means of touchscreen pen strokes, traditional keyboard and mouse operations. The combination of both the main and the feedback data stream is based on the use of Confusion Networks derived from the output of the on-line and off-line handwritten text recognition systems. The use of the proposed combination help to optimise overall performance and usability.