Hi everyone,
I’m building a real-time, two-way Persian voice conversation pipeline for a small robot project (Reachy Mini) with my professor. Current architecture:
fa-IR-FaridNeural voice) — cloud-only
Why LLM/TTS ended up cloud-based: I initially tried qwen2.5:3b locally via Ollama (CPU-only, since my venv’s torch build is CPU-only), but the output quality in Persian was poor — frequent code-switching into English/other languages, incoherent responses. Switching to Qwen2.5-72B via HF Inference API fixed this completely; responses are now coherent and consistently Persian. edge-tts also gives good voice quality.
The problem: My internet connection is very slow and unstable (~0.7 Mbps down), so I’m getting periodic ConnectTimeout errors on the API calls (I’ve added retry logic, which helps but doesn’t eliminate the issue). For a robot that needs to work reliably, I’d like to move both LLM and TTS to fully local inference if possible.
My hardware:
What I’m trying to figure out:
Any pointers to models, quantization strategies, or alternative local Persian TTS projects would be hugely appreciated. Happy to share more details (code, benchmarks) if useful.
Thanks in advance!