Problem
Bengali grammar correction is a low-resource NLP problem where linguistic complexity, dataset scarcity, informal writing, and inconsistent evaluation make progress difficult to compare.
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Research Square ยท September 2024
A Systematic Literature Review on Bengali Grammar Correction System
A review by Muhammad Abu Nadif, Tanzeem Rahat, Aninda Kumar Sharma, Anika Tabassum, Kawser I. Rushee, and Md Shamsur Rahim.
Why It Matters
Bangla is spoken by hundreds of millions of people, but grammar correction systems lag behind richer-resource languages. Better tools can support writing, education, and language technology.
Core Idea
The review consolidates prior work on automated grammar correction systems, including rule-based methods, statistical models, machine learning, and NLP-based approaches.
Main Result
The paper maps methods, challenges, and evaluation indicators such as accuracy, recall, and F1-score, then identifies future research directions for Bengali grammar correction.
What Was Difficult
The review must compare heterogeneous studies whose datasets, metrics, linguistic assumptions, and technology generations are not always aligned.
Resources
Open Directions
- Which benchmark designs make Bengali grammar correction systems comparable?
- How should systems handle dialectal, informal, and code-mixed writing?
- Can educational tools correct grammar without suppressing valid language variation?