Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/71406
Title: Segmentation and recognition of handwritten Pitman shorthand outlines using neural networks
Other Titles: 基于神经网络的在线英文Pitman速记发声字的识别
Authors: Zhu, M 
Chi, Z 
Wang, X
Keywords: Neural networks
Shorthand
Handwriting recognition
Issue Date: 2003
Publisher: 浙江大學學報編輯部
Source: 浙江大学学报. 工学版 (Journal of Zhejiang University. Engineering science), 2003, v. 37, no. 5, p. 532-536 + 550 How to cite?
Journal: 浙江大学学报. 工学版 (Journal of Zhejiang University. Engineering science) 
Abstract: 介绍了一种对英文Pitman速记发声字进行在线分割识别的新方法.该方法在预处理速记手写体的基础上,采用BP神经网络对发声字分割中可能出现的过分割进行检测和纠正,对音素记号/非音素记号和单个音素记号进行分类和识别,并实现了基于单个笔划识别结果的整体单词识别.通过对68个常用英文单词的测试,验证了该方法的平均识别正确率达到89.6%.
Presents a novel approach for segmentation and recognition of on- line vocalized outlines of Pitman shorthand.The approach is to use a trained neural network for the segmentation of the vocalized outlines for the detection of over- segmentation; and to use another trained neural network for the recognition of Pitman shorthand consonant signs; while the word recognition was based on the estimation of the overall confidence on the stroke classification.Experimental results on a test set containing 68 most frequently used English words showed that on average,the approach can achieve an accuracy rate of 89.6%.
URI: http://hdl.handle.net/10397/71406
ISSN: 1008-973X
Rights: © 2003 中国学术期刊电子杂志出版社。本内容的使用仅限于教育、科研之目的。
© 2003 China Academic Journal Electronic Publishing House. It is to be used strictly for educational and research purposes.
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