Modeling Human Performance in Using a Spatial Segmentation Chinese Handwriting Recognizer
نویسندگان
چکیده
To predict and improve human performance in spatial segmentation Chinese handwriting recognizer, a mathematic performance model was developed based on Fitts’ law and probability theory of discrete random variables. The model was verified by a behavioral experiment and it can predict subjects’ task completion time well after the subjects experienced 2 stages of practice (R square > 0.9). The mathematic model including its variants might be very helpful for designers of the user interface to select optimal parameters in layout of elements on the user interface and focus on relatively important and cost-effective factor(s) in the system to optimize the human performance. Further developments of the model in modeling human performance in using other input advices, and its value in developing proactive ergonomic design and analysis tools for input interface design are discussed.
منابع مشابه
Human performance modeling in temporary segmentation Chinese character handwriting recognizers
Human performance in Chinese character handwriting recognizers is critical to the satisfaction and acceptance of their users. Based on Teal’s [CHI’92 (1992) p. 295] interactive model, a static model describing the independent factors in determining the task completion time was set up with a simple mathematical inference; in addition, a dynamic model describing these factors’ direct and indirect...
متن کاملZoning invariant holistic recognizer for hybrid recognition of handwriting
As human handwriting is immensely variable, no single recognition approach appears capable of uniformly good performance. Combining results of multiple recognition approaches gives improved recognition rates. Recognizers used in such a hybrid approach need to be different, so that their results are complementary. Segmentation-based and wholistic recognition approaches are methods which are diff...
متن کاملEffects of Training Set Expansion in Handwriting Recognition Using Synthetic Data
A perturbation model for the generation of synthetic textlines from existing cursively handwritten lines of text produced by human writers is presented. Our goal is to improve the performance of an off-line cursive handwriting recognition system by providing it with additional synthetic training data. It can be expected that by adding synthetic training data the variability of the training set ...
متن کاملRecent Results of Online Japanese Handwriting Recognition and Its Applications
This paper discusses online handwriting recognition of Japanese characters, a mixture of ideographic characters (Kanji) of Chinese origin, and the phonetic characters made from them. Most Kanji character patterns are composed of multiple subpatterns, called radicals, which are shared among many (sometimes hundreds of) Kanji character patterns. This is common in Oriental languages of Chinese ori...
متن کاملOffline cursive handwriting recognition system based on hybrid Markov model and neural networks
An offline cursive handwriting recognition system, based on hybrid of Neural Networks (NN) and Hidden Markov Models (HMM), is described in this paper. Applying SegRec principle, the recognizer does not make hard decision at the character segmentation process. Instead, it delays the character segmentation to the recognition stage by generating a segmentation graph that describes all possible way...
متن کامل