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--- |
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license: mit |
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tags: |
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- NLP |
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--- |
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# Spell-Check Dataset |
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This dataset consists of pairs of misspelled words and their corresponding correctly spelled words, designed for training and evaluating character-level spelling correction models. It is particularly useful for tasks such as: |
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- Spelling correction |
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- Character-level sequence-to-sequence modeling |
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- Error detection and correction in text |
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Each data point in the dataset contains: |
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- misspelled: A misspelled version of a word. |
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- correct: The corrected spelling of the word. |
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## Notes |
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The words were derived from the NLTK words corpus, which provides a comprehensive list of English words. |
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## Synthetic Misspellings |
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Misspellings were programmatically generated using common spelling error patterns, including: |
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- Character swaps: e.g., teh → the. |
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- Extra characters: e.g., thhe → the. |
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- Missing characters: e.g., th → the. |
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- Keyboard proximity errors: e.g., grerb → gerb. |
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## Citation |
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```bibtex |
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@dataset{etheridge2025spellcorrection, |
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author = {Torin Etheridge}, |
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title = {Spell-Correction Dataset: Misspelled to Corrected Word Pairs}, |
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year = {2025}, |
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publisher = {Hugging Face}, |
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journal = {Hugging Face Datasets}, |
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url = {https://huggingface.co/datasets/torinriley/spell-correction}, |
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note = {A dataset for training and evaluating character-level spelling correction models.} |
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} |
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``` |
