| --- |
| library_name: pytorch |
| license: mit |
| pipeline_tag: text-to-speech |
| tags: |
| - accent-tts |
| - mandarin |
| - joycent |
| - grad-tts |
| - whisaid |
| --- |
| |
| # Joycent trained with WhisAID Medium GRL accent embeddings |
|
|
| This is a Joycent Mandarin accent TTS acoustic model trained using accent |
| embeddings extracted by |
| [`walston/whisaid-medium-grl`](https://huggingface.co/walston/whisaid-medium-grl). |
| The released checkpoint is epoch 100. |
|
|
| - **Paper:** [Joycent: Diffusion-based Accent TTS without Accented Phone Prediction](https://huggingface.co/papers/2606.16417) |
| - **Code:** [oshindow/Joycent-code](https://github.com/oshindow/Joycent-code) |
| - **Accent encoder:** [walston/whisaid-medium-grl](https://huggingface.co/walston/whisaid-medium-grl) |
| - **Vocoder:** [walston/joycent-vocoder](https://huggingface.co/walston/joycent-vocoder) |
|
|
| ## Download |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| |
| checkpoint_path = hf_hub_download( |
| repo_id="walston/joycent-medium-grl", |
| filename="grad_100.pt", |
| ) |
| ``` |
|
|
| Pass the downloaded checkpoint to `joycent/inference_joycent.py` with the |
| `--acoustic-checkpoint` argument. Full synthesis also requires the Joycent |
| vocoder and reference-audio feature extraction dependencies described in the |
| Joycent repository. |
|
|
| ## Checkpoint |
|
|
| - Epoch: 100 |
| - Acoustic model: Joycent / Grad-TTS |
| - Accent embedding model: WhisAID Whisper Medium GRL (lambda 0.05) |
| - Accent embedding dimension: 256 |
|
|
| ## 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}, |
| } |
| ``` |
|
|
