Character-level interaction in multimodal computer-assisted transcription of text images

Abstract

To date, automatic handwriting text 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. In this work, multimodal interaction at character-level is studied. Until now, multimodal interaction had been studied only at whole-word level. However, character-level pen-stroke interactions may lead to more ergonomic and friendly interfaces. Empirical tests show that this approach can save significant amounts of user effort with respect to both fully manual transcription and non-interactive post-editing correction.