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FreePad: a novel handwriting-based text input for pen and touch interfaces
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International Conference on Intelligent User Interfaces archive
Proceedings of the 13th international conference on Intelligent user interfaces table of contents
Gran Canaria, Spain
SESSION: Short papers table of contents
Pages 297-300  
Year of Publication: 2008
ISBN:978-1-59593-987-6
Authors
A. Bharath  Hewlett-Packard Labs India, Bangalore, India
Sriganesh Madhvanath  Hewlett-Packard Labs India, Bangalore, India
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
AAAI : Association for the Advancement of Artifical Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The last decade has seen tremendous growth in mobile devices such as Pocket PCs, mobile phones, Tablet PCs and notebooks. Most of these devices enable interaction through a stylus or touch interface, powered by handwriting recognition (HWR) capability. In this paper, we propose a novel input method that addresses some of the issues that arise due to the constraints posed by these devices in accepting handwriting input. For instance, many of the devices have a small writing area making "continuous" input difficult if not impossible, and the process of handwriting input demands significant user attention. The proposed solution is inspired by touch-typing, and appreciably reduces user's effort in the interaction, and it is especially suited for very small writing areas. The approach has been demonstrated using a prototype system that recognizes handwritten English words, and its accuracy has been evaluated using a standard dataset of handwritten words. A preliminary user study has also been carried out to understand user acceptance of the proposed technique.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Jaeger, S., Manke, S., Reichert, J., and Waibel, A. Online handwriting recognition: The NPen++ recognizer. International Journal on Document Analysis and Recognition, 3, (2001), 169--180.
 
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Rabiner, R. A tutorial on Hidden Markov Models and selected applications in speech recognition. Proc. of IEEE, 79(2), (1989), 257--286.

Collaborative Colleagues:
A. Bharath: colleagues
Sriganesh Madhvanath: colleagues