卡纳达语的可读性分析

2019 1st International Conference on Advances in Information Technology (ICAIT) Pub Date : 2019-07-01 DOI:10.1109/ICAIT47043.2019.8987355

Vishwaas Narasinh

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引用次数: 1

摘要

本文提出了一种基于神经网络的方法，在不使用任何预定义词表的情况下预测给定卡纳达语句子的可读性得分。我们使用一年级到十年级的教科书作为输入来训练模型，并且能够获得优于所有最先进方法的相关性。我们还展示并证明了w.r.t可读性分数与每节课所考虑的句子数量之间的一般行为。

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Readability Analysis of Kannada Language

This paper proposes a neural network based approach to predict a readability score for a given sentence in Kannada language without the use of any predefined word list. We have used textbooks of Grade-1 to Grade-10 as input to train the model, and were able to achieve a correlations well above all the state-of-the-art methods. We also show and prove the general behavior of readability scores of w.r.t the number of sentences considered in each class.

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来源期刊

2019 1st International Conference on Advances in Information Technology (ICAIT)

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