Datasets:
configs:
- config_name: default
data_files:
- split: train
path: train.csv
- split: dev
path: dev.csv
- split: test
path: test.csv
STIF-Indonesia
A dataset of "Semi-Supervised Low-Resource Style Transfer of Indonesian Informal to Formal Language with Iterative Forward-Translation".
You can also find Indonesian informal-formal parallel corpus in this repository.
Description
We were researching transforming a sentence from informal to its formal form. Our work addresses a style-transfer from informal to formal Indonesian as a low-resource machine translation problem. We benchmark several strategies to perform the style transfer.
In this repository, we provide the Phrase-Based Statistical Machine Translation, which has the highest result in our experiment. Note that, our data is extremely low-resource and domain-specific (Customer Service domain). Therefore, the system might not be robust towards out-of-domain input. Our future work includes exploring more robust style transfer. Stay tuned!
Paper
You can access our paper below:
Team
- Haryo Akbarianto Wibowo @ Kata.ai
- Tatag Aziz Prawiro @ Universitas Indonesia
- Muhammad Ihsan @ Bina Nusantara
- Alham Fikri Aji @ Kata.ai
- Radityo Eko Prasojo @ Kata.ai
- Rahmad Mahendra @ Universitas Indonesia