Three medium-quality en-US single-speaker Piper TTS voices, each with its .onnx model and .onnx.json config, plus README install instructions. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
59 lines
2.0 KiB
Markdown
59 lines
2.0 KiB
Markdown
# AIVoices_HA
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Custom [Piper](https://github.com/OHF-Voice/piper1-gpl) text-to-speech voices for [Home Assistant](https://www.home-assistant.io/).
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These are medium-quality, single-speaker English (`en-US`) neural voices trained for use with Home Assistant's local TTS engine.
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## Voices
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| Voice | Files | Language | Sample rate | Quality |
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|-------|-------|----------|-------------|---------|
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| **cathy** | `en_us-cathy-medium.onnx` + `.onnx.json` | en-US | 22050 Hz | medium |
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| **cynda** | `en_us-cynda-medium.onnx` + `.onnx.json` | en-US | 22050 Hz | medium |
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| **james** | `en_us-james-medium.onnx` + `.onnx.json` | en-US | 22050 Hz | medium |
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Each voice consists of two files that must stay together:
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- `*.onnx` — the trained model weights
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- `*.onnx.json` — the voice configuration (phoneme map, sample rate, inference settings)
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## Installation (Home Assistant)
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These voices work with the **Piper** add-on / [wyoming-piper](https://github.com/rhasspy/wyoming-piper).
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1. Locate the Piper data directory where custom voices are stored. For the
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official **Piper** add-on this is the share folder, typically:
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```
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/share/piper/
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```
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2. Copy **both** files for each voice you want into that directory:
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```
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en_us-cathy-medium.onnx
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en_us-cathy-medium.onnx.json
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```
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3. Restart the Piper add-on. Then in Home Assistant go to
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**Settings → Voice assistants → (your assistant) → Text-to-speech**
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and select the new voice.
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> Tip: If a voice does not appear, confirm the `.onnx` and `.onnx.json`
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> filenames match exactly and that both files are present.
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## Testing a voice locally
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With Piper installed you can render a sample to a WAV file:
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```bash
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echo "Hello from Home Assistant." | \
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piper --model en_us-cathy-medium.onnx --output_file sample.wav
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```
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## License
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The licensing of a trained Piper voice depends on the dataset it was trained
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on. Add a `LICENSE` file describing the terms that apply to these models and
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their training data before distributing them.
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