whisper-piper-voice

# Whisper + Piper Voice Pipeline Local STT (speech-to-text) and TTS (text-to-speech) as a single HTTP server. Zero cloud dependencies. ## Architecture ``` Audio In → POST /transcribe → Whisper (faster-whisper) → JSON {text, language} Text In → POST /speak → Piper TTS → ffmpeg → audio/ogg (Opus) ``` Both endpoints run in one Python process on one port (default: 9998). ## Quick Start 1. Install dependencies: ```bash python3 -m venv ~/whisper-env && source ~/whisper-env/bin/activate pip install faster-whisper apt install ffmpeg # or brew install ffmpeg on macOS ``` 2. Download Piper + a voice: ```bash mkdir -p ~/piper && cd ~/piper wget https://github.com/rhasspy/piper/releases/latest/download/piper_linux_x86_64.tar.gz tar xzf piper_linux_x86_64.tar.gz mkdir voices && cd voices wget https://huggingface.co/rhasspy/piper-voices/resolve/main/de/de_DE/thorsten_emotional/medium/de_DE-thorsten_emotional-medium.onnx wget https://huggingface.co/rhasspy/piper-voices/resolve/main/de/de_DE/thorsten_emotional/medium/de_DE-thorsten_emotional-medium.onnx.json ``` 3. Run the server (`scripts/voice-server.py`): ```bash python3 voice-server.py --port 9998 \ --whisper-model small --whisper-device cpu \ --piper-bin ~/piper/piper/piper \ --piper-model ~/piper/voices/de_DE-thorsten_emotional-medium.onnx ``` ## API **Transcribe** (audio → text): ```bash curl -X POST -F "file=@message.ogg" http://HOST:9998/transcribe # {"text": "Hallo Welt", "language": "de"} ``` **Speak** (text → audio): ```bash curl -X POST -H "Content-Type: application/json" \ -d '{"text": "Hallo Welt", "speaker": "4"}' \ http://HOST:9998/speak -o response.ogg ``` ## Configuration | Flag | Default | Description | |------|---------|-------------| | `--port` | 9998 | Server port | | `--whisper-model` | small | tiny/base/small/medium/large-v3 | | `--whisper-device` | cpu | cpu or cuda | | `--piper-bin` | (required) | Path to piper binary | | `--piper-model` | (required) | Path to .onnx voice file | | `--piper-speaker` | 4 | Speaker ID (multi-speaker models) | | `--speed` | 0.9 | TTS speed (lower = faster) | ## Choosing Models **Whisper:** `small` for CPU (good balance), `medium` for GPU (best quality without large-v3 overhead). **Piper voices:** Browse https://rhasspy.github.io/piper-samples/ — download .onnx + .onnx.json files. ## Full Setup Guide Read `references/setup-guide.md` for systemd service config, all voice options, model comparison table, and OpenClaw integration details.