Scholarlink

In this paper, we discuss the challenges of implementing spelling correction in resource-scarce languages like Nepali, and propose an ensemble model that combines SymSpell, Soundex, and N-gram LM algorithms to improve accuracy and computational speed. It is one of the pioneering approach in spelling correction in Nepali language as most of the existing researches and implementations have focused on morphological analysis and ruled-based spelling correction. The suggested model achieved an 81% accuracy when tested on Nepali text with 1000 sentences consisting of 16289 words, outperforming Symspell alone which achieved 55% accuracy. The research identifies limitations and suggests future improvements for better spelling correction.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Nepali Word Spelling Correction Using Ensemble Learning Technique

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Samir Bhattarai,
  • Aman Shakya,
  • Basanta Joshi

摘要

In this paper, we discuss the challenges of implementing spelling correction in resource-scarce languages like Nepali, and propose an ensemble model that combines SymSpell, Soundex, and N-gram LM algorithms to improve accuracy and computational speed. It is one of the pioneering approach in spelling correction in Nepali language as most of the existing researches and implementations have focused on morphological analysis and ruled-based spelling correction. The suggested model achieved an 81% accuracy when tested on Nepali text with 1000 sentences consisting of 16289 words, outperforming Symspell alone which achieved 55% accuracy. The research identifies limitations and suggests future improvements for better spelling correction.