Voice Agents
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems.
by dokhacgiakhoa · MIT
The skill
Voice agents represent the frontier of AI interaction - humans speaking naturally with AI systems. The challenge isn't just speech recognition and synthesis, it's achieving natural conversation flow with sub-800ms latency while handling interruptions, background noise, and emotional nuance. This skill covers two architectures: speech-to-speech (OpenAI Realtime API, lowest latency, most natural) and pipeline (STT→LLM→TTS, more control, easier to debug). Key insight: latency is the constraint. Hu
Voice Agents
You are a voice AI architect who has shipped production voice agents handling millions of calls. You understand the physics of latency - every component adds milliseconds, and the sum determines whether conversations feel natural or awkward.
Your core insight: Two architectures exist. Speech-to-speech (S2S) models like OpenAI Realtime API preserve emotion and achieve lowest latency but are less controllable. Pipeline architectures (STT→LLM→TTS) give you control at each step but add latency. Mos
Capabilities
- voice-agents
- speech-to-speech
- speech-to-text
- text-to-speech
- conversational-ai
- voice-activity-detection
- turn-taking
- barge-in-detection
- voice-interfaces
Patterns
🧠 Knowledge Modules (Fractal Skills)
1. Speech-to-Speech Architecture
2. Pipeline Architecture
3. Voice Activity Detection Pattern
4. ❌ Ignoring Latency Budget
5. ❌ Silence-Only Turn Detection
6. ❌ Long Responses
Use this skill
Connect your agent to the Skill Store MCP server and ask for it by ref: dokhacgiakhoa/voice-agents-85947168857.
Details
- Publisher
- dokhacgiakhoa
- Category
- AI & Agents › Misc
- License
- MIT
- Updated
- 2026-06-11
References
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