Selecting llm, stt and tts for your voice agent
About this video
In this video, you’ll learn how to select the right LLM, TTS, and STT for your Voice Agent to ensure accurate understanding, natural responses, and seamless conversations. We walk through how each component plays a critical role — from speech recognition (STT) to response generation (LLM) to voice output (TTS) — helping you build a voice agent that sounds intelligent, responsive, and human-like. ✨ To build your own Voice agent, visit: https://app.kipps.ai/ This tutorial focuses on choosing the best combination of models and voice technologies based on your use case, so you can optimize performance, cost, and user experience. If you’re building voice solutions for customer support, sales, or automation workflows, this is a must-watch to understand how the right tech stack directly impacts your agent’s effectiveness. What You’ll Learn in This Video • Role of LLM, TTS, and STT in Voice Agents • How to choose the right LLM for responses • Selecting TTS for natural and clear voice output • Choosing STT for accurate speech recognition • Balancing quality, latency, and cost • Matching tech stack with use cases • Best practices for optimizing voice performance Real-World Use Case In this setup, the Voice agent: • Accurately converts speech to text using STT • Generates intelligent responses with the LLM • Delivers natural-sounding replies through TTS • Maintains low latency for real-time interaction • Adapts performance based on business needs • Provides a smooth and human-like conversation experience ✨ Know More About Us: Kipps AI is an AI-powered automation platform built to help businesses scale smarter. Our products include Chat Agents, WhatsApp Agents, and Voice Agents designed to handle customer support, sales lead nurturing, appointment booking, follow-ups, onboarding, re-engagement campaigns, and more — automatically and intelligently. With over 2 years of experience in AI automation, we’ve worked with hundreds of clients, continuously optimizing and deploying AI agents that drive real business results.
