Instructions to use softguy777/snap_piper_korean_22k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Piper
How to use softguy777/snap_piper_korean_22k with Piper:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
SNAP Piper Korean Multi-Speaker TTS (22.05kHz, 22 Speakers)
Multi-scale Mel-spectrogram loss fine-tuned high-fidelity VITS ONNX models for Korean speech synthesis. Trained on AI Hub Korean reading dataset with SNAP Frontend Engine phonology & text normalization.
Model Highlights
- Architecture: VITS (Piper) + Multi-Scale Mel Loss Fine-tuning
- Sampling Rate: 22,050 Hz
- Speakers: 22 Voice Actors (11 Male, 11 Female) across age groups 20s to 60s
- Performance: High-speed Real-time inference on CPU with ONNXRuntime (~500+ FPS)
- Checkpoints:
- Male: Step 9,000 Sweet-spot (HNR top 1, Mel L1 3.289, Whisper WER 0%)
- Female: Step 8,000 Sweet-spot (HNR 2.09 dB, DynRange 101.9 dB, Whisper WER 0%)
Files
- snap_male11_reading_22k.onnx & .json : Male 11-speaker FP32 ONNX
- snap_female11_reading_22k.onnx & .json : Female 11-speaker FP32 ONNX
- snap_male11_reading_22k_fp16.onnx : Male 11-speaker FP16 ONNX (~58MB)
- snap_female11_reading_22k_fp16.onnx : Female 11-speaker FP16 ONNX (~58MB)
Demo
Experience live synthesis on Hugging Face Spaces: softguy777/snap_voice_demo2
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