| --- |
| library_name: piper |
| license: cc-by-4.0 |
| language: |
| - it |
| tags: |
| - text-to-speech |
| - tts |
| - piper |
| - checkpoint |
| - finetuning |
| datasets: |
| - committa/serena-synthetic-it-27h |
| --- |
| |
| # it_IT-serena — Piper training checkpoint (Italian, medium) |
| |
| Finetuning base checkpoint for Piper TTS (VITS), trained **from scratch** on Italian. |
| |
| - Model: piper (piper_train), quality **medium**, 22.05 kHz |
| - Base voice: **serena** — female, neutral Standard Italian (no regional accent), synthetic |
| - Training: **94 epochs** from scratch, batch 10, 29,470 clips (27 h) |
| - Dataset: [committa/serena-synthetic-it-27h](https://huggingface.co/datasets/committa/serena-synthetic-it-27h) |
| - File: `epoch=94-step=559930.ckpt` — **keep this filename** (piper_train convention: |
| `epoch=N-step=M`), which tooling uses to pick the highest checkpoint |
| |
| ## Why this checkpoint |
| |
| Piper publishes **no official pretrained checkpoint for Italian** (the `rhasspy/piper-checkpoints` |
| catalog has no `it` entry; the only official Italian voices are `it_IT-paola-medium`, which was |
| finetuned from a U.S. English base, and `it_IT-riccardo-x_low`, trained from scratch at x_low |
| quality — neither exposes a trainable checkpoint). This is the only public Italian **medium** |
| checkpoint that can be used as a finetuning base. |
| |
| ## Sample |
| |
| Audio of the base voice (it_IT-serena-medium): |
|
|
| <audio controls src="https://huggingface.co/committa/it_IT-serena-medium-checkpoint/resolve/main/samples/speaker_0.mp3"></audio> |
|
|
| ## Use as a base for finetuning other Italian voices |
|
|
| Any checkpoint of the same quality config (medium) can be resumed with piper_train: |
| |
| ```sh |
| python -m piper_train \ |
| --dataset-dir /path/to/your_voice_training_folder \ |
| --resume_from_checkpoint epoch=94-step=559930.ckpt \ |
| --quality medium |
| ``` |
| |
| Because the base already speaks Italian (correct phonemes and prosody), a new Italian voice |
| converges in **far fewer epochs** than from scratch — and with less data. This works for |
| **both female and male target voices**: the timbre is learned from the new dataset, so with |
| enough epochs the new voice fully takes over. |
|
|
| ## License |
|
|
| CC-BY-4.0 — derived from [committa/serena-synthetic-it-27h](https://huggingface.co/datasets/committa/serena-synthetic-it-27h). |
| If you use this checkpoint to build a voice, credit the dataset and this model. |
|
|
