Datasets:

Netra-Lab
/

bilingual-en-km

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

Netra Lab

GitHub | Model | Demo

Bilingual English–Khmer Parallel Corpus

4,257,178 English↔Khmer translation examples, in both directions: the training corpus of 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, 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

{"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

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 training/evaluate.sh published --test alt

Sources

Source	License
lyfeyvutha/nllb-en-km-316K	see the original repo
Netra-Lab/khmer-english-pairs-raw	MIT
KrorngAI/ParaCrawl-English-Khmer-v2	see the original repo
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.

@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}
}