Segmentation and recognition of phonetic features in handwritten Pitman shorthand

Authors:
Yang Ma;Graham Leedham;Colin Higgins;Swe Myo Htwe
Affiliations:
School of Computer Engineering, Nanyang Technological University, N4-2A-32 Nanyang Avenue, Singapore;School of Computer Engineering, Nanyang Technological University, N4-2A-32 Nanyang Avenue, Singapore;School of Computer Science and IT, The University of Nottingham, Wollaton Road, Nottingham NG8 1BB, UK;School of Computer Science and IT, The University of Nottingham, Wollaton Road, Nottingham NG8 1BB, UK
Venue:
Pattern Recognition
Year:
2008

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Abstract

There is a wish to be able to enter text into mobile computing devices at the speed of speech. Only handwritten shorthand schemes can achieve this data recording rate. A new, overall solution to the segmentation and recognition of phonetic features in Pitman shorthand is proposed in this paper. Approaches to the recognition of consonant outlines, vowel and diphthong symbols and shortforms, which are different components of Pitman shorthand, are presented. A new rule is introduced to solve the issue of smooth junctions in the consonant outlines which was normally the bottleneck for recognition. Experiments with a set of 1127 consonant outlines, 2039 vowels and diphthongs and 841 shortforms from three shorthand writers have demonstrated that the proposed solution is quite promising. The recognition accuracies for consonant outlines, vowels and diphthongs, and shortforms achieved 75.33%, 96.86% and 91.86%, respectively. From the evaluation of 461 outlines with smooth junction, the introduction of the new rule has a great positive effect on the performance of the solution. The recognition accuracy of smooth junction improves from 37.53% to 93.41% given a writing time increase of 14.42%.