Does it support barge-in detection?

Yes, it includes patterns for implementing barge-in detection, allowing your AI agent to gracefully stop speaking and start listening the moment a user interrupts.

Can this skill help with audio noise and environment issues?

Absolutely. It provides guidance on implementing noise handling and semantic Voice Activity Detection (VAD) to distinguish between background noise and actual user speech.

How does this skill help with conversational latency?

The skill provides a 'latency budget' framework, helping you measure and optimize every millisecond of the audio processing chain to achieve the sub-800ms threshold required for natural human conversation.

What architectures does the Voice Agents skill support?

It supports both Speech-to-Speech (S2S) architectures for the lowest possible latency and emotion preservation, and Pipeline architectures (STT→LLM→TTS) for developers who need more granular control over each processing step.

Voice Agent Architect

Name: Voice Agent Architect
Author: claudiodearaujo

byclaudiodearaujo

•

Data Science & ML

Architects high-performance voice AI systems with optimized latency, natural turn-taking, and robust speech-to-speech workflows.

The Voice Agent Architect skill transforms Claude into a production-focused expert for building conversational AI interfaces. It provides deep technical guidance on the physics of latency, helping developers choose between Speech-to-Speech (S2S) models like OpenAI Realtime for speed, or Pipeline (STT-LLM-TTS) architectures for maximum control. By implementing sophisticated patterns for Voice Activity Detection (VAD), barge-in handling, and semantic turn-taking, this skill ensures AI interactions feel natural, responsive, and human-like in production environments.

Key Features

01Noise handling and semantic audio error mitigation

021 GitHub stars

03Conversational flow management and turn-taking logic

04Latency budget optimization for sub-800ms response targets

05Expertise in Speech-to-Speech (S2S) and Pipeline (STT-LLM-TTS) architectures

06Advanced Voice Activity Detection (VAD) and barge-in implementation

Use Cases

01Developing automated book narration systems with emotional nuance and character voices

02Building real-time customer service voice bots with natural interruption handling

03Implementing hands-free AI interfaces for mobile or IoT devices requiring low-latency feedback

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claudiodearaujo/sistema-de-narra-o-de-livro voice-agents

For use in Claude.ai and ChatGPT

Download Skill