README.md

metadata

license: mit
language:
  - km
tags:
  - text-to-speech
  - tts
  - khmer

SimpleKhmerTTS

Decoder-only transformer TTS, using WavTokenizer as the audio codec and DDD-Cambodia/khmer-speech-dataset as dataset.

Samples

Text	Audio
Sample 1
Sample 2
Sample 3
Sample 4

Setup

git clone https://github.com/FirstPotatoCoder/SimpleKhmerTTS.git
cd SimpleKhmerTTS
pip install -q -r requirements.txt
python scripts/download_weights.py

Run

python examples/run_inference.py " ភាសាខ្មែរមានអក្សរច្រើន ហើយពិបាកសរសេរបន្តិច។ ភាសានេះមានប្រវត្តិយូរអង្វែង និងជាផ្នែកមួយយ៉ាងសំខាន់នៃវប្បធម៌កម្ពុជា។" --speaker_id 0

Or from Python:

from tts.inference import TTSPipeline

pipe = TTSPipeline(
    tts_weights="weights/tts.pt",
    wavtokenizer_weights="weights/wavtokenizer.ckpt",
    wavtokenizer_config="configs/wavtokenizer_config.yaml"
)

pipe.generate(" ភាសាខ្មែរមានអក្សរច្រើន ហើយពិបាកសរសេរបន្តិច។", speaker_id=1, out_path="out.wav")

Limitations

• The model sometimes hallucinates, generating babbling or garbled output on rare or unseen words, making it ill-suited for direct deployment — likely due to the limited amount of training data and codec's limited performance on Khmer audio.
• Works best when generating ~3s to 10s of audio, matching the length distribution of its training data.
• No chunking support yet — the current repo only supports clip-by-clip generation, one sample at a time.

Credits

• Data: Khmer Speech Dataset by DDD-Cambodia

• Compute: Kaggle for free T4 GPU access

• Audio tokenizer/codec: WavTokenizer (vendored under wavtokenizer/, trimmed to inference-only code).