A knowledge-based approach for recognition of handwritten Pitman shorthand language strokes

The Pitman shorthand language (PSL) is a recording medium practised in all organizations, where English is the transaction medium. It has the practical advantage of high speed of recording, more than 120-200 words per minute, because of which it is universally acknowledged. This recording medium has its continued existence in spite of considerable developments in speech processing systems, which are not universally established yet. In order to exploit the vast transcribing potential of PSL a new area of research on automation of PSL processing is conceived. It has three major steps, namely, shape recognition of PSL strokes; their validation and English text production from these strokes. The paper describes a knowledge-based approach for the recognition of PSL strokes. Information about location and the direction of the starting point and final point of strokes are considered the knowledge base for recognition of strokes. The work comprises preprocessing, determination of starting and final points, acquisition of quadrant knowledge, graph-based traversal and finally a rule-based inference process for generating phonetic equivalent of English language characters for the strokes. The proposed work is thoroughly tested for a large number of handwritten strokes.