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Enabling text readability awareness during the micro planning phase of NLG applications

机译：在NLG应用程序的微计划阶段启用文本可读性意识

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Currently, there is a lack of text complexity awareness in NLG systems. Much attention has been given to text simplification. However, based upon results of an experiment, we unveiled that sophisticated readers in fact would rather read more sophisticated text, instead of the simplest text they could get. Therefore, we propose a technique that considers different readability levels during the micro planning phase of an NLG system. Our technique considers grammatical and syntactic choices, as well as lexical items, when generating text. The application uses the domain of descriptive summaries of line graphs as its use case. The technique proposed uses learning for identifying features of text complexity; a graph search algorithm for efficient aggregation given a target reading level, and a combination of language modeling and word vectors for the creation of a domain-aware synset which allows the creation of disambiguated lexicon that is appropriate to different reading levels. We found that generating text at different target reading levels is indeed preferred by readers with varying reading abilities. To the best of our knowledge, this is the first time readability awareness is considered in the micro planning phase of NLG systems.
机译：目前，NLG系统中缺乏文本复杂性意识。已经给予了许多关注文本简化。然而，基于实验的结果，我们推出了成熟的复杂读者宁愿阅读更复杂的文本，而不是他们可以得到的最简单的文本。因此，我们提出了一种在NLG系统的微规划阶段期间考虑不同可读性水平的技术。我们的技术考虑了语法和句法选择，以及生成文本时的词汇项目。该应用程序使用行图的描述性摘要域作为其用例。该技术建议使用学习来识别文本复杂性的特征;一种图形搜索算法，用于给定目标读取级别的高效聚合，以及用于创建域感知综合的语言建模和字向量的组合，允许创建适合于不同读取级别的消歧词。我们发现，在具有不同读取能力的读取器的读卡器中确实优先生成不同目标读数水平的文本。据我们所知，这是第一次在NLG系统的微规划阶段考虑可读性意识。

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