PERCORE: A Deep Learning-Based Framework for Persian Spelling Correction with Phonetic Analysis

• URL: http://arxiv.org/abs/2407.14789v1
• Date: Sat, 20 Jul 2024 07:41:04 GMT
• Title: PERCORE: A Deep Learning-Based Framework for Persian Spelling Correction with Phonetic Analysis
• Authors: Seyed Mohammad Sadegh Dashti, Amid Khatibi Bardsiri, Mehdi Jafari Shahbazzadeh,
• Abstract summary: This research introduces a state-of-the-art Persian spelling correction system that seamlessly integrates deep learning techniques with phonetic analysis. Our methodology effectively combines deep contextual analysis with phonetic insights, adeptly correcting both non-word and real-word spelling errors. A thorough evaluation on a wide-ranging dataset confirms our system's superior performance compared to existing methods.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This research introduces a state-of-the-art Persian spelling correction system that seamlessly integrates deep learning techniques with phonetic analysis, significantly enhancing the accuracy and efficiency of natural language processing (NLP) for Persian. Utilizing a fine-tuned language representation model, our methodology effectively combines deep contextual analysis with phonetic insights, adeptly correcting both non-word and real-word spelling errors. This strategy proves particularly effective in tackling the unique complexities of Persian spelling, including its elaborate morphology and the challenge of homophony. A thorough evaluation on a wide-ranging dataset confirms our system's superior performance compared to existing methods, with impressive F1-Scores of 0.890 for detecting real-word errors and 0.905 for correcting them. Additionally, the system demonstrates a strong capability in non-word error correction, achieving an F1-Score of 0.891. These results illustrate the significant benefits of incorporating phonetic insights into deep learning models for spelling correction. Our contributions not only advance Persian language processing by providing a versatile solution for a variety of NLP applications but also pave the way for future research in the field, emphasizing the critical role of phonetic analysis in developing effective spelling correction system.

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