Hugging Face's logo

Datasets:
Panhapich
/
khmer-tts-processed

Tasks:
Text-to-Speech
Automatic Speech Recognition
Languages:
Khmer
Size:
10K<n<100K
License:
Dataset card Files
xet
 Community
khmer-tts-processed / README.md
Panhapich's picture
Panhapich
Add dataset card
389b849 verified
preview code
|
Raw History Blame Contribute Delete
3.36 kB
metadata 
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 (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:

  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, 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