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  • 标题:A Context-Sensitive Approach to Find Optimum Language Model for Automatic Bangla Spelling Correction
  • 本地全文:下载
  • 作者:Muhammad Ifte Khairul Islam ; Md. Tarek Habib ; Md. Sadekur Rahman
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2018
  • 卷号:9
  • 期号:11
  • DOI:10.14569/IJACSA.2018.091126
  • 出版社:Science and Information Society (SAI)
  • 摘要:Automated spelling correction is an important phenomenon in typing that has intense effect on aiding both literate and semi-literate people while using keyboard or other similar devices. Such automated spelling correction technique also helps students significantly in learning process through applying proper words during word processing. A lot of work has been conducted for English language, but for Bangla, it is still not adequate. All work done so far in Bangla is context-free. Bangla is one of the mostly spoken languages (3.05% of world population) and considered seventh language of all languages in the world. In this paper, we propose a context-sensitive approach for automated spelling correction in Bangla. We make combined use of edit distance and stochastic, i.e. N-gram language model. We use six N-gram models in total. A novel approach is deployed in order to find the optimum language model in terms of performance. In addition, for finding out better performance, a large Bangla corpus of different word types is used. We have achieved a satisfactory and promising accuracy of 87.58%.
  • 关键词:Spelling correction; non-word error; N-gram; edit distance; magnifying search; accuracy
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