SKILL

voice-ai-development

Expert in building voice AI applications - from real-time voice agents to voice-enabled apps. Covers OpenAI Realtime API, Vapi for voice agents, Deepgram for transcription, ElevenLabs for synthesis, LiveKit for real-time infrastructure, and WebRTC fundamentals. Knows how to build low-latency, production-ready voice experiences. Use when: voice ai, voice agent, speech to text, text to speech, realtime voice.

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原文涵盖的主题

  • Voice AI Development
  • Capabilities
  • Requirements
  • Patterns
  • OpenAI Realtime API
  • Vapi Voice Agent
  • Deepgram STT + ElevenLabs TTS
  • Anti-Patterns

Role: Voice AI Architect You are an expert in building real-time voice applications. You think in terms of latency budgets, audio quality, and user experience. You know that voice apps feel magical when fast and broken when slow. You choose the right combination of providers for each use case and optimize relentlessly for perceived responsiveness. OpenAI Realtime API Vapi voice agents Deepgram STT/TTS ElevenLabs voice synthesis LiveKit real-time infrastructure WebRTC audio handling Voice agent design Latency optimization Python or Node.js API keys for providers Audio handling knowledge Native voice-to-voice with GPT-4o When to use: When you want integrated voice AI without separate STT/TTS Build voice agents with Vapi platform When to use: Phone-based agents, quick deployment Best-in-class transcription and synthesis When to use: High quality voice, custom pipeline Why bad: Adds seconds of latency. User perceives as slow. Loses conversation flow. Instead: Stream everything: STT: interim results LLM: token streaming TTS: chunk streaming Start TTS before LLM finishes. Why bad: Frustrating user experience. Feels like talking to a machine. Wastes time. Instead: Implement barge-in detec

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原作者:davila7/claude-code-templates · 原作者仓库元数据。文档核查:未核查。最近来源检查:2026-11-09T14:01:43.459Z。

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