Incorporating Syntactic Constraints in Recognizing Handwritten Sentences
Abstract
The output of handwritten word recognizers (HWR) tends to be very noisy due to various factors. In order to compensate for this behaviour, several choices of the HWR must be initially considered. In the case of handwritten sentence/phrase recognition, linguistic constraints may be applied in order to improve the results of the HWR. This paper discusses two statistical methods of applying syntactic constraints to the output of an HWR on input consisting of sentences/phrases. Both methods are based on syntactic categories (tags) associated with words. The first is a purely statistical method, the second is a hybrid method which combines higher-level syntactic information (hypertags) with statistical information regarding transitions between hypertags.
Cite
Text
Srihari and Baltus. "Incorporating Syntactic Constraints in Recognizing Handwritten Sentences." International Joint Conference on Artificial Intelligence, 1993.Markdown
[Srihari and Baltus. "Incorporating Syntactic Constraints in Recognizing Handwritten Sentences." International Joint Conference on Artificial Intelligence, 1993.](https://mlanthology.org/ijcai/1993/srihari1993ijcai-incorporating/)BibTeX
@inproceedings{srihari1993ijcai-incorporating,
title = {{Incorporating Syntactic Constraints in Recognizing Handwritten Sentences}},
author = {Srihari, Rohini K. and Baltus, Charlotte M.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1993},
pages = {1262-1267},
url = {https://mlanthology.org/ijcai/1993/srihari1993ijcai-incorporating/}
}