| --- |
| language: |
| - km |
| license: cc-by-sa-4.0 |
| task_categories: |
| - text-to-speech |
| - automatic-speech-recognition |
| pretty_name: Khmer TTS Processed (Fish Speech format) |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # Khmer TTS Processed |
|
|
| Preprocessed, Fish Speech-ready Khmer speech data derived from |
| [DDD-Cambodia/khm-asr-cultural](https://huggingface.co/datasets/DDD-Cambodia/khm-asr-cultural) |
| (`train` split). Built for fine-tuning [Fish Speech](https://github.com/fishaudio/fish-speech) |
| (`fishaudio/openaudio-s1-mini`) for Khmer text-to-speech / voice cloning — |
| see [Panhapich/Tuna-TTS](https://huggingface.co/Panhapich/Tuna-TTS) for the |
| resulting model checkpoints. |
|
|
| ## Processing pipeline |
|
|
| Raw audio + transcripts were pulled from the source dataset and run through: |
|
|
| 1. Export/merge raw clips into a single manifest |
| 2. Automated audio-quality (QC) grading |
| 3. Denoising |
| 4. VAD-based silence trimming |
| 5. Loudness normalization |
| 6. Khmer text normalization (numbers, currency, dates, percentages verbalized) |
| 7. Per-speaker stratified train/validation split |
| 8. Conversion to Fish Speech's speaker-folder format (paired `.wav` + `.lab` |
| files, one folder per speaker) |
|
|
| Source code: [Pich09/voice-clone](https://github.com/Pich09/voice-clone), |
| `scripts/01_download_ddd.py` through `scripts/09_convert_to_fish_format.py`. |
|
|
| ## Splits |
|
|
| | Split | Clips | Speakers | Duration | |
| |-------|--------|----------|-----------| |
| | train | 54,083 | 10 | 125.2 h | |
| | valid | 1,123 | 6 | 2.6 h | |
|
|
| ## Repository layout |
|
|
| Each archive is a `.tar` of Fish Speech-format `.wav`/`.lab` pairs (or, for |
| the `ready_*` archives, already VQ-extracted protobuf training shards). |
|
|
| | File | Contents | |
| |---|---| |
| | `processed/khmer_base__khmer_base_v1.tar` | Full train + val set in one archive (raw audio, unsharded, ~22GB) | |
| | `processed/khmer_base__khmer_base_v1__shard{0..5}of6.tar` | Train set split into 6 raw-audio shards (~3.5GB each) | |
| | `processed/khmer_base__khmer_base_v1__val.tar` | Validation set (raw audio, unsharded, ~430MB) | |
| | `processed/khmer_base__khmer_base_v1__ready_shard{i}of6.tar` | VQ-extracted + packed protobuf training data for shard `i` (much smaller than raw audio — ready to train on directly, no VQ extraction needed) | |
| | `processed/khmer_base__khmer_base_v1__ready_val.tar` | VQ-extracted + packed protobuf validation data | |
| | `processed/khmer_base__khmer_base_v1__shards.json` | Shard-count manifest | |
| | `processed/khmer_base__khmer_base_v1__ready.json` | Tracks which shards have completed VQ preprocessing | |
|
|
| The shard split exists to fit Kaggle's 20GB `/kaggle/working` disk cap, which |
| can't hold the full ~22GB dataset at once — see |
| `kaggle/preprocess_khmer_vq_v2.ipynb` in the source repo for how shards are |
| VQ-preprocessed one at a time, and `kaggle/train_khmer_base.ipynb` / |
| `scripts/10_train_fish_khmer_base.sh` for how the data is consumed in |
| training. |
|
|
| ## Audio quality |
|
|
| QC grading is automated (signal-based heuristics), not manually verified per |
| clip — treat grades as a filtering signal, not a guarantee of studio quality. |
|
|
| ## License |
|
|
| The source dataset is licensed **CC BY-SA 4.0**. This derived/processed |
| version is distributed under the same license and its share-alike terms. |
|
|
| ## Citation |
|
|
| Please cite the original dataset: |
|
|
| ``` |
| DDD-Cambodia/khm-asr-cultural, https://huggingface.co/datasets/DDD-Cambodia/khm-asr-cultural |
| ``` |
|
|
