Handwriting recognition using semantic information

Attempts to improve the performance of handwriting recognition systems have often involved the exploitation of linguistic constraints such as syntax or semantics. In either case, successful implementation requires the creation of a lexical database containing the relevant information. However, to create a database of semantic information from scratch for a realistically sized vocabulary is an enormous task which is a major reason why so many semantic theories fail to "scale up" from the small, artificial domains in which they were developed. A better approach is to use existing sources of semantic information, such as machine-readable dictionaries (from which definitions may be extracted) and text corpora (from which collocations may be derived). This paper describes the development of techniques that use such resources to improve the performance of handwriting recognition systems.