Text Augmentation

The transforms.noise module provides noise-based data augmentation operators for Persian text. These are useful for training robust NLP models by simulating real-world text corruption such as OCR errors, keyboard typos, and irregular whitespace.

Operator	Description
KeyboardNoise	Replaces characters with visually or positionally adjacent keys on a Persian keyboard layout
OCRNoise	Substitutes characters with visually similar ones to simulate OCR scanning errors
WhitespaceNoise	Randomly inserts, removes, or alters whitespace between words and subwords

Example Usage

from shekar import WhitespaceNoise, OCRNoise, KeyboardNoise

text = "عمری دگر بباید بعد از وفات ما را"

keyboard_noise = KeyboardNoise()
print(keyboard_noise(text))

ocr_noise = OCRNoise()
print(ocr_noise(text))

white_noise = WhitespaceNoise()
print(white_noise(text))

عمریی دگر بباید بعد از وفات ما را
عمری ذگر بباید بعد از وفات ما را
عمری‌دگر بباید‌بعد‌از وفاتما را

Note

The output of each operator is stochastic, results will vary between runs. Use a fixed random seed during experiments to ensure reproducibility.