Character-Level Interaction in Computer-Assisted Transcription of Text Images

To date, automatic handwriting recognition systems are far from being perfect and heavy human intervention is often required to check and correct the results of such systems. As an alternative, an interactive framework that integrates the human knowledge into the transcription process has been presented in previous works. This new approach follows an Interactive Predictive paradigm and our results show that significant amounts of human effort can be saved. Until now only whole-word interactions with this system have been considered. In this work, character-level keystroke interactions, that can allow for a more ergonomic and friendly interfaces, are proposed. Empirical results show that this allows for further improvements in user productivity.