Vocal Chat

**Quick judgment**: Solid, focused skill for enabling walkie-talkie style, voice-to-voice WhatsApp conversations using local ASR and TTS. It is a good fit when you explicitly want WhatsApp audio interactions and can manage the required local toolchain. **Strengths** - Clean, well-defined workflow: incoming audio → local transcription → LLM response → local TTS → WhatsApp voice reply. - Uses local tools only, which is attractive for privacy-sensitive or self-hosted environments. - Always sends both text and audio, improving usability and debuggability of voice interactions. **Key risks / limitations** - Strong dependency on local environment setup (ffmpeg, whisper-cpp, sherpa-onnx-tts); misconfiguration will break the loop. - No explicit mention of robust error handling (e.g., failed transcription, TTS errors, long audios, or WhatsApp API failures) or content filtering. - Performance and transcription quality will vary significantly with hardware and chosen models; maintaining RTF < 0.5 may not hold on low-end machines. - Appears specialized to WhatsApp audio workflows; not a generic voice interface for multiple channels. **Recommended scenarios** - You are building a WhatsApp-based voice assistant or “walkie-talkie mode” bot and can control the hosting environment. - You need local-only audio processing for privacy, compliance, or cost reasons. - You are okay with some engineering effort to install, configure, and monitor whisper-cpp, ffmpeg, and sherpa-onnx-tts, and you can add your own safeguards (monitoring, logging, and content policies) around it.