README.md

---
language: 
- min
- ind
pretty_name: Minangnlp Mt
task_categories: 
- machine-translation
tags: 
- machine-translation
---

In this work, we create Minangkabau–Indonesian (MIN-ID) parallel corpus by using Wikipedia. We obtain 224,180 Minangkabau and
510,258 Indonesian articles, and align documents through title matching, resulting in 111,430 MINID document pairs.
After that, we do sentence segmentation based on simple punctuation heuristics and obtain 4,323,315 Minangkabau sentences. We
then use the bilingual dictionary to translate Minangkabau article (MIN) into Indonesian language (ID'). Sentence alignment is conducted using
ROUGE-1 (F1) score (unigram overlap) (Lin, 2004) between ID’ and ID, and we pair each MIN sentencewith an ID sentence based on the highest ROUGE1.
We then discard sentence pairs with a score of less than 0.5 to result in 345,146 MIN-ID parallel sentences.
We observe that the sentence pattern in the collection is highly repetitive (e.g. 100k sentences are about biological term definition). Therefore,
we conduct final filtering based on top-1000 trigram by iteratively discarding sentences until the frequency of each trigram equals to 100. Finally, we
obtain 16,371 MIN-ID parallel sentences and conducted manual evaluation by asking two native Minangkabau speakers to assess the adequacy and
fluency (Koehn and Monz, 2006). The human judgement is based on scale 1–5 (1 means poor quality and 5 otherwise) and conducted against 100 random
samples. We average the weights of two annotators before computing the overall score, and we achieve 4.98 and 4.87 for adequacy and fluency respectively.
This indicates that the resulting corpus is high-quality for machine translation training.


## Languages

min, ind

## Supported Tasks

Machine Translation

## Dataset Usage
### Using `datasets` library
```
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/minangnlp_mt", trust_remote_code=True)
```
### Using `seacrowd` library
```import seacrowd as sc
# Load the dataset using the default config
dset = sc.load_dataset("minangnlp_mt", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("minangnlp_mt"))
# 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://github.com/fajri91/minangNLP](https://github.com/fajri91/minangNLP)

## Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

## Dataset License

MIT

## Citation

If you are using the **Minangnlp Mt** dataloader in your work, please cite the following:
```
@inproceedings{koto-koto-2020-towards,
    title = "Towards Computational Linguistics in {M}inangkabau Language: Studies on Sentiment Analysis and Machine Translation",
    author = "Koto, Fajri  and
      Koto, Ikhwan",
    booktitle = "Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation",
    month = oct,
    year = "2020",
    address = "Hanoi, Vietnam",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.paclic-1.17",
    pages = "138--148",
}


@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}
}

```