---
license: unknown
language: 
- tha
pretty_name: Alice Thi
task_categories: 
- optical-character-recognition
tags: 
- optical-character-recognition
---

ALICE-THI is a Thai handwritten script dataset that contains 24045 character
images, which is split into Thai handwritten character dataset (THI-C68) for
14490 images and Thai handwritten digit dataset (THI-D10) for 9555 images. The
data was collected from 150 native writers aged from 20 to 23 years old. The
participants were allowed to write only the isolated Thai script on the form and
at least 100 samples per character. The character images obtained from this
dataset generally have no background noise.


## Languages

tha

## Supported Tasks

Optical Character Recognition

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/alice_thi", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("alice_thi", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("alice_thi"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
```

More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).


## Dataset Homepage

[https://www.ai.rug.nl/~mrolarik/ALICE-THI/](https://www.ai.rug.nl/~mrolarik/ALICE-THI/)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

Unknown (unknown)

## Citation

If you are using the **Alice Thi** dataloader in your work, please cite the following:
```
@article{SURINTA2015405,
    title = "Recognition of handwritten characters using local gradient feature descriptors",
    journal = "Engineering Applications of Artificial Intelligence",
    volume = "45",
    number = "Supplement C",
    pages = "405 - 414",
    year = "2015",
    issn = "0952-1976",
    doi = "https://doi.org/10.1016/j.engappai.2015.07.017",
    url = "http://www.sciencedirect.com/science/article/pii/S0952197615001724",
    author = "Olarik Surinta and Mahir F. Karaaba and Lambert R.B. Schomaker and Marco A. Wiering",
    keywords = "Handwritten character recognition, Feature extraction, Local gradient feature descriptor,
    Support vector machine, k-nearest neighbors"
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}

```