- generate_voices.py: scan /config/speakers and /voices recursively,
support .ogg and .m4a (M4A auto-converted via ffmpeg), sanitise voice IDs
- auto_transcribe.py: scan both host paths recursively, support all formats,
use parakeet-asr on port 8010
- docker-compose.yml: mount /home/sparky/Projekte/TTS_Voices/speakers as
/voices, add faster-qwen3-tts-voicedesign service on port 8021
- run_voicedesign_server.py: OpenAI-compatible server for VoiceDesign model
- voicedesign_voices.json: 8 British/German VoiceDesign voices
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Run Qwen3-TTS with CUDA graph acceleration on NVIDIA DGX Spark
(ARM64 / SM 121 / CUDA 13) as an OpenAI-compatible TTS API server.
- Dockerfile targeting nvidia/cuda:13.0.2-base-ubuntu24.04 with ARM64 cu130 PyTorch wheels
- Patch for max-seq-len support to handle long reference audio without crashes
- OpenWebUI + SillyTavern compatible API endpoints (/v1/models, /v1/audio/voices, /speakers)
- Voice management: auto-generate voices.json from speaker reference audio files
- Auto-transcription helper script for generating reference text from audio
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
