| --- |
| 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. |
| |
|  |
| |
| 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. |
| |
