license: cc-by-sa-3.0
language:
- tha
pretty_name: Thai Romanization
task_categories:
- transliteration
tags:
- transliteration
The Thai Romanization dataset contains 648,241 Thai words that were transliterated into English, making Thai pronounciation easier for non-native Thai speakers. This is a valuable dataset for Thai language learners and researchers working on Thai language processing task. Each word in the Thai Romanization dataset is paired with its English phonetic representation, enabling accurate pronunciation guidance. This facilitates the learning and practice of Thai pronunciation for individuals who may not be familiar with the Thai script. The dataset aids in improving the accessibility and usability of Thai language resources, supporting applications such as speech recognition, text-to-speech synthesis, and machine translation. It enables the development of Thai language tools that can benefit Thai learners, tourists, and those interested in Thai culture and language.
Languages
tha
Supported Tasks
Transliteration
Dataset Usage
Using datasets library
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/thai_romanization", trust_remote_code=True)
Using seacrowd library
# Load the dataset using the default config
dset = sc.load_dataset("thai_romanization", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("thai_romanization"))
# 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.kaggle.com/datasets/wannaphong/thai-romanization/data
Dataset Version
Source: 1.0.0. SEACrowd: 2024.06.20.
Dataset License
Creative Commons Attribution Share Alike 3.0 (cc-by-sa-3.0)
Citation
If you are using the Thai Romanization dataloader in your work, please cite the following:
@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}
}