Synthetic Error Dataset Generation Mimicking Bengali Writing Pattern
This addresses the cumbersome process of creating error datasets for Bengali spell checkers, which is crucial for improving their accuracy in text correction applications.
The researchers tackled the problem of manually generating error datasets for Bengali spell checkers by developing an algorithm that automatically creates misspelled Bengali words from correct ones, analyzing writing patterns on QWERTY keyboards.
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.