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How to Build an AI Voice Assistant: A Practical Guide Using Eleven v4

·2026.10.27 21:00

Key point

A practical guide details how to build an AI voice assistant using Eleven v4 Turbo and Scribe v2 Realtime to achieve low-latency, high-accuracy interactions.

Details

  • The article provides a step-by-step guide for building enterprise-grade AI voice assistants, utilizing ElevenLabs' Eleven v4 model for synthesis and Scribe v2 Realtime for transcription.
  • The recommended architecture connects Speech to Text (STT), an LLM, and Text to Speech (TTS) into a real-time pipeline to maintain response latency under 500ms.
  • ElevenLabs Scribe v2 Realtime converts speech to text in under 150ms (excluding network time) using Voice Activity Detection (VAD), while Eleven v4 Turbo synthesizes audio in approximately 100ms.
  • The guide contrasts the Raw API approach, which offers full control over LLM selection and orchestration, with the managed ElevenAgents platform, which integrates tools like Twilio, Salesforce, and HubSpot for no-code deployment.
  • Key implementation steps include defining business roles, implementing Retrieval-Augmented Generation (RAG) for context, and establishing safety guardrails for human handoff and caller verification.
  • Post-deployment metrics focus on containment rate, escalation rate, word error rate (WER), hallucination rate, and Customer Satisfaction (CSAT) to drive iterative improvement.
elevenlabstext-to-speechspeech-to-textragvoice-aielevenagentstutorialreal-time-pipeline
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