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README.md
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- speech-synthesis
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- Basque
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- piper
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- speech-synthesis
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- Basque
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- piper
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---
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# Basque TTS: Maider (Piper Version)
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This repository contains a [Piper](https://github.com/OHF-Voice/piper1-gpl) compatible version of the **Maider** Basque text-to-speech model. The original model was developed by **HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory** (University of the Basque Country UPV/EHU).
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This version has been exported/trained specifically for use with the Piper TTS engine, a fast, local neural text-to-speech engine.
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## Model Details
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- **Language:** Basque (eu)
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- **Speaker:** Maider (Female)
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- **Architecture:** VITS (Optimized for Piper)
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- **Original Credits:** HiTZ Center / Aholab (Project ILENIA)
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- **Format:** Piper (`.onnx` and `.onnx.json` config)
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## Training Details
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- **Architecture:** VITS
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- **Training Engine:** Piper (PyTorch Lightning)
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- **Iterations:** 22 epochs
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- **Sample Rate:** 22050 Hz
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- **Phonemization:** espeak-ng (Basque)
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## Files Included
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* `eu-maider-medium.onnx`: The exported model for fast inference.
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* `eu-maider-medium.onnx.json`: The configuration file (includes phoneme map and synthesis settings).
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* `epoch=22-step=258750.ckpt`: The PyTorch Lightning checkpoint from the 22nd iteration (useful for further training/fine-tuning).
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## Usage
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### Using Piper CLI
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You can run the model locally using the Piper binary:
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```bash
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echo "Kaixo, hau Maider da, Piper motorra erabiliz euskaraz hitz egiten." | \
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./piper --model eu-maider-medium.onnx --output_file output.wav
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```
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### Python API
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```Python
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from piper.voice import PiperVoice
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voice = PiperVoice.load("eu-maider-medium.onnx", "eu-maider-medium.onnx.json")
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with open("output.wav", "wb") as f:
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voice.synthesize_wav("Gaur egun eguzkitsua dugu.", f)
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```
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## Original Model & Data Source
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The base model belongs to the Aholab TTS collection. All voices in this collection are based on the VITS architecture proposed by Kim et al. (2021).
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Maider & Antton: Developed by HiTZ with funding from Project ILENIA.
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License: Public Creative Commons Attribution 4.0 (for the voice resource) and Apache License 2.0 (for the code/model).
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## Authors & Credits
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The original Maider model was created by:
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HiTZ Basque Center for Language Technology - Aholab Signal Processing Laboratory, University of the Basque Country EHU.
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