---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*

task_categories:
- automatic-speech-recognition
- text-classification

language:
- km

pretty_name: Cultural Khmer ASR Dataset

size_categories:
- 100K<n<1M

license: cc-by-sa-4.0
---

# Khmer ASR Cultural Dataset

727.94 hours of manually curated speech-text pairs by native speakers in the Khmer language about Cambodian cultural topics. On average, each recording is 8 seconds. Speaker metadata (gender, age group, and origin city) is provided.

- Language: Khmer (khm).
- Source(s): Native speakers from Cambodia (5 females, 7 males). The utterances were manually generated based on topics and subtopics listed in metadata.
- Domain(s): Cultural domain, with a total of 61 topics and 1,749 subtopics.
- Size: 495.9GB data instances
- WAV file names are formatted as: `{speaker_id}_khm_{sentence_id}.wav`.

## Sample

The first row of our metadata.csv:

| Topic | Subtopic | Speaker ID | Paragraph ID | Sentence ID | Sentences |
|-------|----------|------------|--------------|-------------|------------|
| Recipes | Street food dishes | f-adt1-0001 | 1 | recipes_01_0001_0001 | មុខម្ហូបតាមដងផ្លូវ គឺជាមុខម្ហូបមួយមានភាពសម្បូរបែប និងមានភាពងាយស្រួល ដែលគេពេញនិយមក្នុងការបរិភោគ ថែមទាំងមានតម្លៃសមរម្យ។ |

Index 0 of our dataset:

```
{
  'speaker_id': 'f-adt1-0001',
  'topic': 'Recipes',
  'subtopic': 'Street food dishes',
  'paragraph_id': 1,
  'sentence_id': 'recipes_01_0001_0001',
  'transcript': 'មុខម្ហូបតាមដងផ្លូវ គឺជាមុខម្ហូបមួយមានភាពសម្បូរបែប និងមានភាពងាយស្រួល ដែលគេពេញនិយមក្នុងការបរិភោគ ថែមទាំងមានតម្លៃសមរម្យ។',
  'audio': {
    'path': '<audio_path>',
    'array': array([ 1.17741292e-05, -6.42662635e-05, -2.19850161e-04, ...,
        1.00613176e-03,  9.77945630e-04,  0.00000000e+00], shape=(138949,)),
    'sampling_rate': 16000
  },
  'duration': 8.6843125
}
```

**Khmer ASR Cultural Dataset** is also available on [Mozilla Data Collective](https://datacollective.mozillafoundation.org/datasets/cml9h5vgc01bxmn075sjeftek).

## Use cases

### Automatic speech recognition (ASR)

Off-the-shelf state-of-the-art multilingual automatic speech recognition pre-trained models (e.g., [OpenAI's Whisper](https://huggingface.co/collections/openai/whisper-release)) cannot transcribe Khmer well. Even with further fine-tuning, the error rate (lower is better, 0% means no errors/perfect) for Khmer ASR is far from usable [(Lovenia, 2025)](https://arxiv.org/pdf/2406.10118). See the `khm` column in Figure 3 below.

![image](https://cdn-uploads.huggingface.co/production/uploads/616cd2e040e2f69baa1c7af2/CbVshGEs23FqaXROuKn25.png)

To have a good automatic speech recognition (ASR) model for Khmer, you will require a large amount of speech-text pairs in Khmer. However, before **Khmer ASR Cultural Dataset** is available, there was only one Khmer speech-text dataset: [OpenSLR 42](https://openslr.org/42/) with 3.97 hours of speech-text pairs (male only).

Our preliminary experiment shows that even only by adding 650 speech-text pairs from DDD's dataset to the training data, we can decrease the Whisper models' CER by around 0.46%-0.74% compared to only using OpenSLR 42 in the training data. Now the Whisper Large V2's performance in Khmer drops to only 8.11% CER. With more speech-text pairs collected by DDD, ASR models' performance in Khmer will definitely be able to transcribe Khmer audios with even less errors.

### Other potential use cases

**Khmer ASR Cultural Dataset** can also be used to train models on Khmer text-to-speech (TTS), language modeling, topic modeling, and next sentence prediction.

## Attribution

**Khmer ASR Cultural Dataset**'s license is Creative Commons Attribution Share Alike 4.0 International (CC-BY-SA-4.0). Please attribute **Digital Divide Data** if you use this dataset in any way.