| --- |
| license: cc-by-4.0 |
| task_categories: |
| - translation |
| language: |
| - en |
| - km |
| tags: |
| - translation |
| - machine-translation |
| - khmer |
| - english |
| - bilingual |
| - netra-lab |
| pretty_name: Bilingual English–Khmer Parallel Corpus |
| size_categories: |
| - 1M<n<10M |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-*.parquet |
| - split: validation |
| path: data/validation-*.parquet |
| --- |
| |
| <p align="center"> |
| <img src="https://huggingface.co/datasets/Netra-Lab/bilingual-en-km/resolve/main/assets/header.png" width="260" alt="Netra Lab" /> |
| </p> |
|
|
| <hr> |
|
|
| <p align="center"> |
| <a href="https://github.com/netra-ai-lab/Netra-NMT"><b>GitHub</b></a> | |
| <a href="https://huggingface.co/Netra-Lab/Netra-NMT"><b>Model</b></a> | |
| <a href="https://huggingface.co/spaces/Darayut/Netra-NMT"><b>Demo</b></a> |
| </p> |
|
|
| # Bilingual English–Khmer Parallel Corpus |
|
|
| 4,257,178 English↔Khmer translation examples, in both directions: the training corpus of |
| [Netra NMT](https://huggingface.co/Netra-Lab/Netra-NMT), a 77M-parameter translation model. Four public |
| English–Khmer datasets were merged, deduplicated and length-filtered (about 2.4M unique pairs), and every |
| pair appears once per direction. One row is one example: a source with a direction marker and its target. |
|
|
| **Code:** [github.com/netra-ai-lab/Netra-NMT](https://github.com/netra-ai-lab/Netra-NMT), with the recipe |
| that built it (`training/netra_nmt_train/scripts/recipe/`). |
|
|
| | Split | Examples | Files | |
| | --- | ---: | --- | |
| | `train` | 4,214,606 | `data/train-*.parquet` | |
| | `validation` | 42,572 | `data/validation-*.parquet` | |
|
|
| | Column | | |
| | --- | --- | |
| | `source` | the input, after a direction marker: `<2km>` (English, translate into Khmer) or `<2en>` (Khmer, translate into English) | |
| | `target` | the reference translation | |
|
|
| ```json |
| {"source": "<2km> A year later, the scientists were able to detect these waves.", "target": "មួយឆ្នាំក្រោយមក អ្នកវិទ្យាសាស្ត្រអាចរកឃើញរលកទាំងនេះ។"} |
| {"source": "<2en> សីតុណ្ហភាពប្រតិបត្តិការ -20 ~ 55 ℃", "target": "Operating Temperature -20~55℃"} |
| ``` |
|
|
| ## Use |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("Netra-Lab/bilingual-en-km", split="train") |
| ``` |
|
|
| ## How Netra NMT used it |
|
|
| The rows keep their natural casing and unsegmented Khmer. Before training, the recipe |
| (`08c_build_casenorm_dataset.py`, `08d_build_kmseg_from_casenorm.py`) lowercases English sources and |
| word-segments Khmer with khmercut on both sides. `netra-nmt-train prepare` applies the same rules to your |
| own pairs. |
|
|
| The model is scored on a separate set, the ALT test split (`mutiyama/alt`, 1,018 pairs), not on this |
| validation split: |
|
|
| ```bash |
| bash training/evaluate.sh published --test alt |
| ``` |
|
|
| ## Sources |
|
|
| | Source | License | |
| | --- | --- | |
| | [lyfeyvutha/nllb-en-km-316K](https://huggingface.co/datasets/lyfeyvutha/nllb-en-km-316K) | see the original repo | |
| | [Netra-Lab/khmer-english-pairs-raw](https://huggingface.co/datasets/Netra-Lab/khmer-english-pairs-raw) | MIT | |
| | [KrorngAI/ParaCrawl-English-Khmer-v2](https://huggingface.co/datasets/KrorngAI/ParaCrawl-English-Khmer-v2) | see the original repo | |
| | [SeyhaLite/Translate-English-Khmer-All](https://huggingface.co/datasets/SeyhaLite/Translate-English-Khmer-All) | Apache-2.0 | |
|
|
| ## License |
|
|
| This card is CC BY 4.0. The text keeps the terms of the source it came from (table above); check them |
| before redistribution or commercial use, and cite the sources. |
|
|
| ```bibtex |
| @misc{bilingual_en_km, |
| title = {Bilingual English--Khmer Parallel Corpus}, |
| author = {Nhem Darayut}, |
| year = {2026}, |
| howpublished = {\url{https://huggingface.co/datasets/Netra-Lab/bilingual-en-km}}, |
| note = {Combined from lyfeyvutha/nllb-en-km-316K, Netra-Lab/khmer-english-pairs-raw, |
| KrorngAI/ParaCrawl-English-Khmer-v2, and SeyhaLite/Translate-English-Khmer-All} |
| } |
| ``` |
|
|
