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Human identification of letters in mixed-script handwriting: an upper bound on recognition rates

机译:人工识别混合脚本手写体中的字母:识别率的上限

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This paper focuses on a reading task consisting of the identification of letters in mixed-script handwritten words. This task is performed by humans using extended or limited linguistic context. Their performance rate is to give an upper bound on recognition rates of computer programs designed to recognize handwritten letters in mixed-script writing. Many recognition algorithms are being developed in the research community, and there is a need for establishing ways to compare them. As some effort is on its way to give large test sets with standard formats, we propose an algorithm to determine a test set of reduced size that is appropriate for the task to achieve (the type of texts or words to be recognized). Also, with respect to a particular task, we propose a method for finding an upper limit to the letter recognition rate to aim for.
机译:本文的重点是阅读任务,包括识别混合脚本手写单词中的字母。该任务由人类使用扩展或受限的语言环境来执行。它们的性能率是设计用来识别混合脚本书写中的手写字母的计算机程序的识别率的上限。研究社区正在开发许多识别算法,并且需要建立比较它们的方法。由于正在努力提供具有标准格式的大型测试集,因此我们提出了一种算法,用于确定尺寸缩小的测试集,该测试集适合于要完成的任务(要识别的文本或单词的类型)。此外,针对特定任务,我们提出了一种用于寻找目标字母识别率上限的方法。

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