Off-Line Cursive Script Word Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-organized language modeling for speech recognition
Readings in speech recognition
Fundamentals of speech recognition
Fundamentals of speech recognition
Conjoined location and recognition of street names within a postal address delivery line
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
A2iA Check Reader: A Family of Bank Check Recognition Systems
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
A Full English Sentence Database for Off-Line Handwriting Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Writer adaptation techniques in HMM based off-line cursive script recognition
Pattern Recognition Letters
Ensemble methods to improve the performance of an English handwritten text line recognizer
SACH'06 Proceedings of the 2006 conference on Arabic and Chinese handwriting recognition
Interactive layout analysis and transcription systems for historic handwritten documents
Proceedings of the 10th ACM symposium on Document engineering
Combining neural networks to improve performance of handwritten keyword spotting
MCS'10 Proceedings of the 9th international conference on Multiple Classifier Systems
Attention-Feedback Based Robust Segmentation of Online Handwritten Isolated Tamil Words
ACM Transactions on Asian Language Information Processing (TALIP)
Handwriting recognition in historical documents using very large vocabularies
Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing
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In this paper, a system for the reading of totally unconstrained handwritten text is presented. The kernel of the system is a hidden Markov model (HMM) for handwriting recognition. The HMM is enhanced by a statistical language model. Thus linguistic knowledge beyond the lexicon level is incorporated in the recognition process. Another novel feature of the system is that the HMM is applied in such a way that the difficult problem of segmenting a line of text into individual words is avoided. A number of experiments with various language models and large vocabularies have been conducted. The language models used in the system were also analytically compared based on their perplexity.