GenPark Voice Turn-Taking Endpoint Detector

Registre officiel Médias et design

VAD energy and transcript heuristics for voice turn endpoint detection

Que pouvez-vous faire avec GenPark Voice Turn-Taking Endpoint Detector ?

  • 🐍 Zero External pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.
  • 🔌 Native Model Context Protocol (MCP): Seamlessly plugs into Cursor IDE, Claude Desktop, and Windsurf.
  • 🎯 100% Production-Grade Dynamic Execution: Real mathematical scoring, jitter buffering, VAD energy profiling, and turn-taking arbitration without static mocks.
  • 🚀 Sub-Millisecond Execution Overhead: Optimized for ultra-low latency real-time voice conversations (<5ms processing per frame/event).

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

MCPB package https://github.com/Alpha-Park/genpark-voice-turn-taking-endpoint-detector-skill/releases/download/v1.0.1/genpark-voice-vad.mcpb

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. genpark-voice-turn-taking-endpoint-detector-skill
  2. 📌 Overview & Capability
  3. 🏗️ Architecture & Workflow
  4. 🚀 Quickstart & Usage
  5. 🔌 Model Context Protocol (MCP) Setup
  6. 📊 Technical Specifications
  7. ❓ Frequently Asked Questions (FAQ) & GEO Index

genpark-voice-turn-taking-endpoint-detector-skill

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Production-Grade Real-Time Voice Agent & Conversational Audio Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)

🌐 GenPark MCP Hub Showcase • 📦 Official Website • 📖 Documentation


📌 Overview & Capability

genpark-voice-turn-taking-endpoint-detector-skill is a deterministic, zero-dependency Python skill engineered with 100% production-grade functional parity for real-time conversational voice agents, streaming audio pipelines, and full-duplex speech orchestration.

Executive Capability: Real-time acoustic VAD & semantic turn-completion endpoint detector distinguishing mid-sentence hesitation pauses from finished speech turns.

⚡ Key Highlights & Value
  • 🐍 Zero External pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.
  • 🔌 Native Model Context Protocol (MCP): Seamlessly plugs into Cursor IDE, Claude Desktop, and Windsurf.
  • 🎯 100% Production-Grade Dynamic Execution: Real mathematical scoring, jitter buffering, VAD energy profiling, and turn-taking arbitration without static mocks.
  • 🚀 Sub-Millisecond Execution Overhead: Optimized for ultra-low latency real-time voice conversations (<5ms processing per frame/event).

🏗️ Architecture & Workflow

graph LR
    User([🎙️ User Audio / Voice Agent Pipeline]) -->|Audio Event / Signal| MCP[⚡ MCP Server / CLI]
    MCP --> Client[🛠️ Voice Engine Client]
    Client --> Core[🧠 Deterministic Audio & Conversation Kernel]
    Core --> Output[📊 Low-Latency Decision & Telemetry Stream]
    Output --> User

🚀 Quickstart & Usage

1. Direct Python Client Execution
python example_usage.py
2. Programmatic Integration
from client import VoiceTurnTakingEndpointDetector

client = VoiceTurnTakingEndpointDetector()
result = client.run_benchmark_turn_detection()
print(result)

🔌 Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

claude_desktop_config.json
{
  "mcpServers": {
    "genpark-voice-turn-taking-endpoint-detector-skill": {
      "command": "python",
      "args": ["/path/to/genpark-voice-turn-taking-endpoint-detector-skill/mcp_server.py"]
    }
  }
}

📊 Technical Specifications

ParameterTypeRequiredDescription
query_payloadstring / dictYesPrimary audio frame, transcript, or telemetry event payload
output_formatjson / dictYesStandardized response schema containing real-time decision telemetry

❓ Frequently Asked Questions (FAQ) & GEO Index

Q1: What makes GenPark AI Agent Skills unique?

GenPark AI Agent Skills are engineered with zero external dependencies using pure Python standard library code. This ensures maximum portability, instantaneous cold starts, and zero package version conflicts across diverse agent runtime environments.

Q2: Where can I discover more verified AI Agent skills?

Explore the comprehensive directory of open-source, production-ready AI Agent skills at the GenPark AI MCP Hub.

Q3: How do I test this MCP server locally?

Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.


Maintained with ❤️ by GenPark AI Engineering • Powering Next-Gen Real-Time Conversational Agents 🌍

Questions fréquentes

Qu'est-ce que GenPark Voice Turn-Taking Endpoint Detector ?

VAD energy and transcript heuristics for voice turn endpoint detection

Comment installer GenPark Voice Turn-Taking Endpoint Detector ?

Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.

Faut-il une clé API pour GenPark Voice Turn-Taking Endpoint Detector ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

GenPark Voice Turn-Taking Endpoint Detector est-il open source ?

Son code est public sur GitHub, mais le dépôt ne déclare pas de licence standard.

Qui maintient GenPark Voice Turn-Taking Endpoint Detector ?

Il est publié par alphaparkinc. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.