27Group/noisy_zarma

Zarma Noisy Dataset Overview The Zarma Noisy Dataset is a collection of Zarma sentences with artificially introduced noise to simulate human-like errors. This dataset is designed for tasks such as grammatical error correction (GEC), text denoising, and robustness testing in natural language processing (NLP) for low-resource languages like Zarma. It is derived from a clean monolingual Zarma dataset (monolingual_zarma.jsonl) by applying various types of noise… See the full description on the dataset page: https://huggingface.co/datasets/27Group/noisy_zarma.