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committa/it_IT-serena-high-checkpoint
it_IT-serena-high-checkpoint is a text-to-speech model from committa. Use it when you need text read aloud. It is set up for piper. The card lists the license as cc-by-4.0.
Finetuning base checkpoint for Piper TTS (VITS), fine-tuned on Italian.
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.ckpt998 MB · 100%
From the Hugging Face model README
Finetuning base checkpoint for Piper TTS (VITS), fine-tuned on Italian.
committa/serena-synthetic-it-28h (30,842 clips, 28 h)epoch=18-step=105450.ckpt — piper_train convention: epoch=N-step=M,
which tooling uses to pick the highest checkpointPiper publishes no official pretrained checkpoint for Italian (the rhasspy/piper-checkpoints
catalog has no it entry). This is the only public Italian high checkpoint that can be
used as a finetuning base. It is the base used to build it_IT-serena-high, and it is
fine-tuned on an extended dataset (serena-synthetic-it-28h) with targeted
sentence-initial phrases for improved prosody at the start of sentences.
Audio of the base voice (it_IT-serena-high):
<audio controls src="https://huggingface.co/committa/it_IT-serena-high-checkpoint/resolve/main/samples/speaker_0.mp3"></audio>
Any checkpoint of the same quality config (high) can be resumed with piper_train:
python -m piper_train \
--dataset-dir /path/to/your_voice_training_folder \
--resume_from_checkpoint epoch=18-step=105450.ckpt \
--quality high
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.
CC-BY-4.0 — derived from committa/serena-synthetic-it-28h. If you use this checkpoint to build a voice, credit the dataset and this model.