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Khmer TTS Processed
Preprocessed, Fish Speech-ready Khmer speech data derived from
DDD-Cambodia/khm-asr-cultural
(train split). Built for fine-tuning Fish Speech
(fishaudio/openaudio-s1-mini) for Khmer text-to-speech / voice cloning —
see Panhapich/Tuna-TTS for the
resulting model checkpoints.
Processing pipeline
Raw audio + transcripts were pulled from the source dataset and run through:
- Export/merge raw clips into a single manifest
- Automated audio-quality (QC) grading
- Denoising
- VAD-based silence trimming
- Loudness normalization
- Khmer text normalization (numbers, currency, dates, percentages verbalized)
- Per-speaker stratified train/validation split
- Conversion to Fish Speech's speaker-folder format (paired
.wav+.labfiles, one folder per speaker)
Source code: 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
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