| library_name: parallel-wavegan | |
| license: mit | |
| pipeline_tag: audio-to-audio | |
| tags: | |
| - vocoder | |
| - parallel-wavegan | |
| - joycent | |
| - mandarin | |
| - 16khz | |
| # Joycent ParallelWaveGAN Vocoder | |
| This repository stores the ParallelWaveGAN vocoder used by Joycent Mandarin accent text-to-speech inference, as presented in the paper [Joycent: Diffusion-based Accent TTS without Accented Phone Prediction](https://huggingface.co/papers/2606.16417). | |
| The model generates 16 kHz audio from 80-bin mel spectrograms. | |
| - **Official Code:** [oshindow/Joycent-code](https://github.com/oshindow/Joycent-code) | |
| - **Project Page:** [Demos](https://anonymous-accent-tts.github.io/Joycent-demo/) | |
| ## Usage | |
| Keep `checkpoint-50000steps.pkl` and `config.yml` in the same directory when loading the model with ParallelWaveGAN: | |
| ```python | |
| import yaml | |
| from parallel_wavegan.utils import load_model | |
| with open("config.yml", encoding="utf-8") as file: | |
| config = yaml.load(file, Loader=yaml.Loader) | |
| vocoder = load_model("checkpoint-50000steps.pkl", config) | |
| vocoder.remove_weight_norm() | |
| vocoder.eval() | |
| ``` | |
| The Joycent implementation and inference instructions are available in the [official repository](https://github.com/oshindow/Joycent-code). | |
| ## Citation | |
| ```bibtex | |
| @misc{wang2026joycentdiffusionbasedaccenttts, | |
| title={Joycent: Diffusion-based Accent TTS without Accented Phone Prediction}, | |
| author={Xintong Wang and Ye Wang}, | |
| year={2026}, | |
| eprint={2606.16417}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.SD}, | |
| } | |
| ``` |