IAM-OnDB - an On-Line English Sentence Database Acquired from Handwritten Text on a Whiteboard
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Efficient BP Algorithms for General Feedforward Neural Networks
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
A flexible system for document processing and text transcription
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
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The recognition performance of current automatic offline handwriting transcription systems is far from being perfect. This is the reason why there is a growing interest in assisted transcription systems, which are more efficient than correcting by hand an automatic transcription. A recent approach to interactive transcription involves multimodal recognition, where the user can supply an online transcription of some of the words. In this paper, a description of the bimodal engine, which entered the "Bi-modal Handwritten Text Recognition" contest organized during the 2010 ICPR, is presented. The proposed recognition system uses Hidden Markov Models hybridized with neural networks (HMM/ANN) for both offline and online input. The N-best word hypothesis scores for both the offline and the online samples are combined using a log-linear combination, achieving very satisfying results.