Effective balancing error and user effort in interactive handwriting recognition

Autores UPV


Transcription of handwritten text documents is an expensive and time-consuming task. Unfortunately, the accuracy of current state-of-the-art handwriting recognition systems cannot guarantee fully-automatic high quality transcriptions, so we need to revert to the computer assisted approach. Although this approach reduces the user effort needed to transcribe a given document, the transcription of handwriting text documents still requires complete manual supervision. An especially appealing scenario is the interactive transcription of handwriting documents, in which the user defines the amount of errors that can be tolerated in the final transcribed document. Under this scenario, the transcription of a handwriting text document could be obtained efficiently, supervising only a certain number of incorrectly recognised words. In this work, we develop a new method for predicting the error rate in a block of automatically recognised words, and estimate how much effort is required to correct a transcription to a certain user-defined error rate. The proposed method is included in an interactive approach to transcribing handwritten text documents, which efficiently employs user interactions by means of active and semi-supervised learning techniques, along with a hypothesis recomputation algorithm based on constrained Viterbi search. Transcription results, in terms of trade-off between user effort and transcription accuracy, are reported for two real handwritten documents, and prove the effectiveness of the proposed approach.