Segmentation-Free Speech Text Recognition for Comic Books

Abstract

Speech text in comic books is written in a particular manner by the scriptwriter which raises unusual challenges for text recognition. We first detail these challenges and present different approaches to solve them. We compare the performances of pre-trained OCR and segmentation-free approach for speech text of comic books written in Latin script. We demonstrate that few good quality pre-trained OCR output samples, associated with other unlabeled data with the same writing style, can feed a segmentation-free OCR and improve text recognition. Thanks to the help of the lexicality measure that automatically accept or reject the pretrained OCR output as pseudo ground truth for a subsequent segmentation-free OCR training and recognition.