Thai2Rom
Thai romanization using LSTM encoder-decoder model with attention mechanism
v0.1
Model Details
- Developer: Chakri Lowphansirikul
- This report author: Wannaphong Phatthiyaphaibun
- Model date: 2019-08-11
- Model version: 0.1
- Used in PyThaiNLP version: 2.1 +
- Filename:
~/pythainlp-data/thai2rom-pytorch-attn-v0.1.tar - GitHub: https://github.com/PyThaiNLP/pythainlp/pull/246
- Train Notebook: https://github.com/lalital/thai-romanization/blob/master/notebook/thai_romanize_pytorch_seq2seq_attention.ipynb
- LSTM Model
- Dataset: https://github.com/lalital/thai-romanization/blob/master/dataset/data.new
- License: CC0
Intended Use - conversion of thai text to the Roman.
Factors - Based on known problems with thai natural Language processing.
Metrics - Evaluation metrics include precision, recall and f1-score.
Training Data Thai2Rom trainset
Evaluation Data
Thai2Rom testset
Quantitative Analyses
The model was evaluated with 3 metrics including F1-score, Exact match, Exact match at character level on the validation set (20% of the dataset or 129,642 examples).
- F1 (macro-average): 0.987
- Exact match: 0.883
- Exact match (Character-level): 0.949
Ethical Considerations
no ideas
Caveats and Recommendations
- Thai text only