README.md

---
dataset_info:
  features:
  - name: inputs
    dtype: string
  - name: targets
    dtype: string
  splits:
  - name: train
    num_bytes: 61501042
    num_examples: 40000
  - name: test
    num_bytes: 15405020
    num_examples: 10000
  download_size: 34451480
  dataset_size: 76906062
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
license: cc-by-sa-3.0
task_categories:
- text2text-generation
- text-generation
language:
- th
size_categories:
- 10K<n<100K
---

# Thai Misspell Correction

This dataset was create from VISTEC-TP-TH-21 dataset. It can use for training Thai Misspell correction model or LLM model.

Use case: Thai Misspell correction

- inputs: Text
- targets: Text correction 

Domain: social media

VISTEC-TP-TH-21 dataset: [https://github.com/mrpeerat/OSKut/tree/main/VISTEC-TP-TH-2021](https://github.com/mrpeerat/OSKut/tree/main/VISTEC-TP-TH-2021)



## Citation

```
@inproceedings{limkonchotiwat-etal-2021-handling,
    title = "Handling Cross- and Out-of-Domain Samples in {T}hai Word Segmentation",
    author = "Limkonchotiwat, Peerat  and
      Phatthiyaphaibun, Wannaphong  and
      Sarwar, Raheem  and
      Chuangsuwanich, Ekapol  and
      Nutanong, Sarana",
    booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.findings-acl.86",
    doi = "10.18653/v1/2021.findings-acl.86",
    pages = "1003--1016",
}
```