voice-ai

Name: voice-ai
Availability: InStock
Author: rkz91

Build low-latency voice agents with Speech-to-Speech and Pipeline architectures.

264|11|Updated Apr 25, 2026

Search Tags:#architecture #voice #real-time #latency #tts #stt #provider-integration

Ready to run

npx skills add https://github.com/rkz91/coco --skill voice-ai-rkz91

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: voice-ai
Source: https://github.com/rkz91/coco/tree/main/skills/voice-ai
Command: npx skills add https://github.com/rkz91/coco --skill voice-ai-rkz91

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Building real-time voice AI systems that feel natural requires tight latency and robust handling across multiple components and providers.

Core Features & Use Cases

Two architectures: Speech-to-Speech for ultra-low latency and Pipeline (STT->LLM->TTS) for greater control and extensibility.
Provider patterns: OpenAI Realtime, Vapi, Deepgram, ElevenLabs, and LiveKit with practical integration guidance.
Latency optimization: streaming STT, LLM, and TTS to minimize end-to-end delay, plus VAD and barge-in support for natural turn-taking.

Quick Start

Prototype a voice-enabled agent using the pipeline architecture (STT->LLM->TTS) with Deepgram for STT and ElevenLabs for TTS to achieve responsive real-time conversations.

Frequently Asked Questions about voice-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a low-latency voice AI agent for real-time conversations?▼

Build a low-latency voice AI agent using streaming Speech-to-Speech or Pipeline (STT->LLM->TTS) architectures with provider patterns for OpenAI Realtime, Deepgram, ElevenLabs, and LiveKit to minimize end-to-end delay.

What's the best way to reduce end-to-end voice latency when integrating STT and TTS?▼

Reduce end-to-end voice latency by streaming STT, LLM, and TTS components simultaneously, implementing Voice Activity Detection (VAD) and barge-in support for natural turn-taking.

When should I choose a Pipeline architecture over Speech-to-Speech for my voice agent?▼

Choose Pipeline architecture (STT->LLM->TTS) for greater control and extensibility, or Speech-to-Speech architecture for ultra-low latency requirements in real-time voice AI systems.

Can I integrate Deepgram and ElevenLabs together in a real-time voice pipeline?▼

Yes, integrate Deepgram for STT and ElevenLabs for TTS in a pipeline architecture to prototype responsive real-time conversations with Python or Node.js and API keys.

Do I need real-time streaming capabilities to implement a voice-enabled agent?▼

Yes, real-time voice AI systems require real-time streaming capabilities in Python or Node.js, plus API keys for chosen providers like OpenAI Realtime, Vapi, Deepgram, ElevenLabs, or LiveKit.

Does this voice AI architecture support barge-in and natural turn-taking?▼

Yes, the voice AI architecture supports barge-in and natural turn-taking through Voice Activity Detection (VAD) and streaming components to minimize end-to-end delay in real-time conversations.