Abstract
In this paper, we introduce a new approach to the computer transcription of handwritten Pitman shorthand as a rapid means of text entry (up to 100 words per minute) into today’s handheld devices, almost at the rate of speech. It is different from previous applications of the same framework from two aspects: – firstly, a novel idea of using geometric attributes other than phonetic attributes in the abstraction of a phonetic Pitman’s shorthand lexicon is proposed. Secondly, a Bayesian network representation for the organisation of shorthand-outline models is introduced, in which natural variability of Pitman shorthand is defined via different nodes and links. Using a probabilistic Bayesian network, the system shows a noticeable robustness not only in transcribing a variety of genuine handwriting, but also in estimating missing vowel components that may have been omitted in speed writing. The accuracy of the new approach (92.86%) is a considerable improvement over previous applications.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Toshiyuki, M.: POBox: An efficient text input method for handheld and ubiquitous computers. In: Proc. of the ACM Conference on Human Factors in Computing System (CHI 1998), Los Angeles, USA, pp. 328–335 (April 1998)
Perlin, K.: Quick writing: Continuous stylus-based text entry. In: Proc. Of the ACM Symposium on User Interface Software and Technology (UIST 1998), Santafe, NM, pp. 215–216 (November 1998)
Leedham, C.G., Downton, A.C.: Automatic recognition of Transcription of Pitman’s Handwritten shorthand. In: Plamondon, R., Leedham, C.G. (eds.) Computer Processing of Handwriting, pp. 235–269. World Scientific, Singapore (1990)
Qiao, Y., Leedham, C.G.: Segmentation and recognition of handwritten Pitman shorthand outlines using an interactive heuristic search. Pattern Recognition 26(3), 433–441 (1993)
Zhu, M., Chi, Z., Wang, X.P.: Segmentation and recognition of on-line Pitman shorthand outlines using neural network. In: Proc. International Conference on Neural Information Processing, Singapore, November 18-22, vol. 5, pp. 2454–2458 (2002)
Yang, M., Leedham, G., Higgins, C., Htwe, S.M.: Segmentation and recognition of phonetic features in handwritten Pitman shorthand. In: submitted to Pattern Recognition (August 2004); (accepted for publication December 2004)
Yang, M., Leedham, G., Higgins, C., Htwe, S.M.: Segmentation and recognition of vocalized outlines in Pitman shorthand. In: Proceedings of the 17th International Conference on Pattern Recognition, Cambridge, UK, August 23-26, vol. I, ISBN 0-7695-2128-2, pp. 441–444 (2004)
Nagabhushan, P., Anami, B.: A knowledge-based approach for recognition of handwritten Pitman shorthand language strokes. Sadhana, Journal of Indian Academy of Sciences 27(Part 5), 685–698 (2002)
Nagabhushan, P., Anami, B.: Dictionary Supported Generation of English Text from Pitman Shorthand Scripted Phonetic Text. Language engineering conference, Hyderabad, India, 33 (December 13-15 2002)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers, Inc., San Mateo (1988)
Xiao, X., Leedham, G.: Signature verification using a modified Bayesian Network. Pattern recognition 35, 983–995 (2002)
Cho, S.J., Kim, J.H.: Bayesian network modelling of strokes and their relatioinships for on-line handwriting recognition. Pattern Recognition 37, 253–264 (2004)
Htwe, S.M., Higgins, C., Leedham, G., Yang, M.: Post Processing of Handwriting Pitman’s Shorthand using Unigram and Heuristic Approaches. In: Marinai, S., Dengel, A.R. (eds.) DAS 2004. LNCS, vol. 3163, pp. 332–336. Springer, Heidelberg (2004)
Htwe, S.M., Higgins, C., Leedham, G., Yang, M.: Evaluation of Feature Sets in the Post Processing of Handwritten Pitman’s Shorthand. In: Proceedings of the 9th International Workshop on Frontiers in Handwriting Recognition, Kokubunji, Tokyo, Japan, October 26-29, pp. 359–364 (2004) ISBN 0-7695-2187-8
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Htwe, S.M., Higgins, C., Leedham, G., Yang, M. (2005). Post Processing of Handwritten Phonetic Pitman’s Shorthand Using a Bayesian Network Built on Geometric Attributes. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Data Mining. ICAPR 2005. Lecture Notes in Computer Science, vol 3686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11551188_63
Download citation
DOI: https://doi.org/10.1007/11551188_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28757-5
Online ISBN: 978-3-540-28758-2
eBook Packages: Computer ScienceComputer Science (R0)