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Measuring Repetitiveness in Texts, a Preliminary Investigation

机译：测量文本中的重复性，初步调查

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摘要

In this paper, a model is presented for the automatic measurement that can systematically describe the usage and function of the phenomenon of repetition in written text. The motivating hypothesis for this study is that the more repetitive a text is, the easier it is to memorize. Therefore, an automated measurement index can provide feedback to writers and for those who design texts that are often memorized including songs, holy texts, theatrical plays, and advertising slogans. The potential benefits of this kind of systematic feedback are numerous, the main one being that content creators would be able to employ a standard threshold of memorizability. This study explores multiple ways of implementing and calculating repetitiveness across levels of analysis (such as paragraph-level or sub-word level) genres (such as songs, holy texts, and other genres) and languages, integrating these into the a model for the automatic measurement of repetitiveness. The Avestan language and some of its idiosyncratic features are explored in order to illuminate how the proposed index is applied in the ranking of texts according to their repetitiveness.
机译：本文提出了一种用于自动测量的模型，该模型可以系统地描述书面重复现象的用法和功能。这项研究的动机假设是，文本越重复，记忆就越容易。因此，自动测量索引可以为作家和设计文本的人提供反馈，这些文本经常被记住，包括歌曲，神圣文本，戏剧和广告口号。这种系统反馈的潜在好处是众多的，主要的好处是内容创建者将能够采用可记忆性的标准阈值。这项研究探索了跨分析级别（例如段落级别或子词级别），流派（例如歌曲，神圣文本和其他流派）和语言实现和计算重复性的多种方法，并将这些方法整合到了模型中自动测量重复性。为了阐明拟议的索引如何根据其重复性应用于文本排名，对Avestan语言及其某些特有功能进行了探讨。

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