On-Line Handy Handwriting Chinese Characters Input for Non-Chinese Speakers Based on Wavelet Neural Network

Abstract

Non-Chinese speakers hold increasing opportunities and need to process Chinese information and communicate in Chinese. This paper, with the purpose of facilitating the handwriting input of Chinese characters for non-Chinese speakers, is directed towards the development of the handwriting rules and vocabulary for Latin-style anti-cursive characters and the ways of their selection and classification. This aims to build a practical platform by utilizing three characteristics of wavelet neural network — automatically ascertaining the number of hidden layer unit, converging rapidly and never running into the partial minimum of networks — for a simple Latin-style online handwriting input and processing, meanwhile, taking the customary handwriting habits of non-Chinese speakers. The paper, based on profound information of cursive characters, deciphered the genetic code of ancient cursive symbols and made clear the rules for characters changing into its cursive style. As a result, it breaks the bottleneck, which enables non-Chinese speakers to easily input information through handwriting Chinese characters.