Statistical methods for speech recognition
Statistical methods for speech recognition
An Omnifont Open-Vocabulary OCR System for English and Arabic
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Subsequential Transducers for Pattern Recognition Interpretation Tasks
IEEE Transactions on Pattern Analysis and Machine Intelligence
HMM-KNN Word Recognition Engine for Bank Cheque Processing
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Amount Translation and Error Localization in Check Processing Using Syntax-Directed Translation
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I
Spontaneous handwriting text recognition and classification using finite-state models
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
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The problem of continuous handwritten text (CHT) recognition using standard continuous speech recognition technology is considered. Main advantages of this approach are a) system development is completely based on well understood training techniques and b) no segmentation of sentence or line images into characters or words is required, neither in the training nor in the recognition phases. Many recent papers address this problem in a similar way. Our work aims at contributing to this trend in two main aspects: i) We focus on the recognition of individual, isolated characters using the very same technology as for CHT recognition in order to tune essential representation parameters. The results are themselves interesting since they are comparable with state-of-the-art results on the same standard OCR database. And ii) all the work (except for the image processing and feature extraction steps) is strictly based on a well known and widely available standard toolkit for continuous speech recognition.