Evaluation of feature sets in the post processing of handwritten Pitman´s shorthand

Innovative ways to rapidly input text becomes essential in today´s world of mobile computing. The paper discusses the computer transcription of handwritten Pitman shorthand as a means of rapid text entry to pen-based computers, particularly from the aspect of linguistic post processing. Feature-to-phoneme conversion is introduced as the first stage of a text interpreter and the application of various production rules based on different pattern structures is discussed. It demonstrates that phoneme ordering is compulsory in dictionary-based transcription and the use of an approximate pattern-matching algorithm resolves the problem of recognition confusion between similar patterns. Experimental results are promising and demonstrate an overall accuracy of 84%.