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A Novel Secant Based Method for Recognition of Handwritten Pitman Shorthand Language Consonants and Vowels

机译:一种基于剪辑手写的Pitman速记语言辅音和元音的新型剪辑方法

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Pitman Shorthand Language (PSL) is a phonetic based language developed in 1837 to translate speech into text. Recognition of text recorded in PSL is an interesting research problem. The PSL has the practical advantage of high speed of recording, more than 120-200 words per minute, because of which it is universally acknowledged. This recording medium has its continued existence inspite of considerable developments in speech processing systems, which are not universally established yet. In order to exploit the vast transcribing potential of PSL a new area of research on automation of PSL processing is conceived. In this work, we have proposed the secant based method for recognition of PSL characters. The work comprises of preprocessing such as thinning and filling, determination of end points of the handwritten strokes. Slope of the strokes are determined using end points of the stroke. Characters are classified based on the estimated slopes of secants and other features such as stroke type and thickness. The vowels are classified based on the vowel type such as dash or dot and thickness and position with respect to a stroke. The proposed work is thoroughly tested for a large number of handwritten strokes. The recognition rates are estimated and found to be in the range of 60 to 95%.
机译:Pitman速记语言(PSL)是1837年开发的基于语音的语言,将演讲转化为文本。在PSL中记录的文本的识别是一个有趣的研究问题。 PSL具有高速记录的实际优势,每分钟超过120-200字,因为它是普遍承认的。该录音介质在语音处理系统中具有相当大的开发的持续存在,这尚未普遍建立。为了利用PSL的巨大转录潜力,构思了PSL处理自动化研究的新研究领域。在这项工作中,我们提出了基于SECANT的方法来识别PSL字符。该工作包括预处理,例如稀释和填充,确定手写笔划的终点。使用中风的终点确定行程的斜率。基于估计的剪辑和其他特征(如行程类型和厚度)分类字符。基于元音类型,例如划线或点和厚度和相对于行程的位置来分类元音。拟议的工作彻底测试了大量手写笔划。估计识别率并发现其范围为60%至95%。

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