Writer adaptation techniques in HMM based Off-Line Cursive Script Recognition

@article{Vinciarelli2002WriterAT,
  title={Writer adaptation techniques in HMM based Off-Line Cursive Script Recognition},
  author={Alessandro Vinciarelli and Samy Bengio},
  journal={Pattern Recognition Letters},
  year={2002},
  volume={23},
  pages={905-916}
}
This work presents the application of HMM adaptation techniques to the problem of Off-Line Cursive Script Recognition. Instead of training a new model for each writer, one first creates a unique model with a mixed database and then adapts it for each different writer using his own small dataset. Experiments on a publicly available benchmark database show that an adapted system has an accuracy higher than 80% even when less than 30 word samples are used during adaptation, while a system trained… CONTINUE READING
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