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e-Article

A Novel Secant Based Method for Recognition of Handwritten Pitman Shorthand Language Consonants and Vowels
Document Type
Conference
Source
2006 International Conference on Advanced Computing and Communications Advanced Computing and Communications, 2006. ADCOM 2006. International Conference on. :292-297 Dec, 2006
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Components, Circuits, Devices and Systems
Handwriting recognition
Speech recognition
Natural languages
Character recognition
Computer science
Speech processing
Automation
Text recognition
Filling
Application software
Optical character recognition
Secant method
Pitman shorthand language
Primitives
Language
Abstract
Pitman Shorthand Language (PSL) is a phonetic based language developed in 1837 to translate speech into text. Recognition of text recorded in PSL is an interesting research problem. The PSL 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 inspite 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. In this work, we have proposed the secant based method for recognition of PSL characters. The work comprises of preprocessing such as thinning and filling, determination of end points of the handwritten strokes. Slope of the strokes are determined using end points of the stroke. Characters are classified based on the estimated slopes of secants and other features such as stroke type and thickness. The vowels are classified based on the vowel type such as dash or dot and thickness and position with respect to a stroke. The proposed work is thoroughly tested for a large number of handwritten strokes. The recognition rates are estimated and found to be in the range of 60 to 95 %.