Synthetic Error Dataset Generation Mimicking Bengali Writing Pattern
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Abstract (arXiv)
While writing Bengali using English keyboard, users often make spelling mistakes. The accuracy of any Bengali spell checker or paragraph correction module largely depends on the kind of error dataset it is based on. Manual generation of such error dataset is a cumbersome process. In this research, We present an algorithm for automatic misspelled Bengali word generation from correct word through analyzing Bengali writing pattern using QWERTY layout English keyboard. As part of our analysis, we have formed a list of most commonly used Bengali words, phonetically similar replaceable clusters, frequently mispressed replaceable clusters, frequently mispressed insertion prone clusters and some rules for Juktakkhar (constant letter clusters) handling while generating errors.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Mar 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
4 papers.
- 2022Bengali Common Voice Speech Dataset for Automatic Speech Recognitioncited by 6
- 2022BSpell: A CNN-Blended BERT Based Bangla Spell Checkercited by 3
- 2021Paradigm Shift in Language Modeling: Revisiting CNN for Modeling Sanskrit Originated Bengali and Hindi Languagecited by 0
- 2026Beyond Clean Text: Evaluating Encoder and Decoder Robustness for Bangla Event Detection in Noisy Textcited by 0
- 2026Beyond Clean Text: Evaluating Encoder and Decoder Robustness for Bangla Event Detection in Noisy Text29 Jun 2026
- 2022BSpell: A CNN-Blended BERT Based Bangla Spell Checker20 Aug 2022
- 2022Bengali Common Voice Speech Dataset for Automatic Speech Recognition28 Jun 2022
- 2021Paradigm Shift in Language Modeling: Revisiting CNN for Modeling Sanskrit Originated Bengali and Hindi Language25 Oct 2021