CONF vincia01conf/IDIAP Writer adaptation techniques in HMM based Off-Line Cursive Script Recognition Vinciarelli, Alessandro Bengio, Samy EXTERNAL http://publications.idiap.ch/attachments/reports/2001/rr01-15.pdf PUBLIC http://publications.idiap.ch/index.php/publications/showcite/vincia01a Related documents Proceedings of 8$^{th}$ International Conference on Frontiers on Handwriting Recognition 2002 Niagara on the Lake (Canada) 287-291 IDIAP-RR 01-15 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 using the data of the single writer only needs at least 200 words in order to achieve the same performance as the adapted models. REPORT vincia01a/IDIAP Writer adaptation techniques in HMM based Off-Line Cursive Script Recognition Vinciarelli, Alessandro Bengio, Samy EXTERNAL http://publications.idiap.ch/attachments/reports/2001/rr01-15.pdf PUBLIC Idiap-RR-15-2001 2001 IDIAP 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 using the data of the single writer only needs at least 200 words in order to achieve the same performance as the adapted models.