it_IT-serena β€” 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 β€” 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
  • File: epoch=94-step=559930.ckpt β€” 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 β€” 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):

Use as a base for finetuning other Italian voices

Any checkpoint of the same quality config (medium) can be resumed with piper_train:

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 β€” 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 β€” derived from committa/serena-synthetic-it-27h. If you use this checkpoint to build a voice, credit the dataset and this model.

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Dataset used to train committa/it_IT-serena-medium-checkpoint