Clustering-based Bangla spell checker

Prianka Mandal, B. M. Hossain
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引用次数: 20

Abstract

Detecting spelling errors and correcting those errors automatically is a great research challenge. Developing a precise spell checker for Bangla language which detects spelling errors and provides suggestions for correcting those errors, is quite difficult because of the complex rules of Bangla spelling. In this paper, a clustering-based spell checking technique is proposed for Bangla language that reduces both search space and search time. Therefore, it improves the performance of a spell checker. The proposed spell checker can handle both typographical errors and phonetic errors. To evaluate the proposed spell checking technique, we use 2,450 misspelled words and the result shows that the proposed approach performs better for checking and correcting spelling errors. The success rate of proposed spell checker is 99.8%. We compare our spell checking technique with two Bangla spell checkers, Avro and Puspa and the proposed system provides relatively better results.
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基于聚类的孟加拉语拼写检查器
检测拼写错误并自动纠正这些错误是一个巨大的研究挑战。由于孟加拉语的拼写规则复杂,开发一个精确的拼写检查器来检测拼写错误并提供纠正这些错误的建议是相当困难的。本文提出了一种基于聚类的孟加拉语拼写检查技术,减少了搜索空间和搜索时间。因此,它提高了拼写检查器的性能。所建议的拼写检查器可以处理印刷错误和语音错误。为了评估所提出的拼写检查技术,我们使用了2,450个拼写错误的单词,结果表明所提出的方法在检查和纠正拼写错误方面表现更好。所提出的拼写检查器的成功率为99.8%。我们将我们的拼写检查技术与两个孟加拉语拼写检查器Avro和Puspa进行了比较,发现我们提出的系统提供了相对更好的结果。
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