Build Voice Agents From Scratch (Course + Research starter kit)

Build real-time AI voice agents using ASR, TTS, LLMs, tools, memory and streaming pipelines with Vizuara’s practical engineering bootcamp.

Build Production-Ready Voice Agents from the Ground Up

Want to create AI receptionists, meeting assistants or conversational agents—but need more than a basic API tutorial?

Build Voice Agents From Scratch by Vizuara AI Labs is a technical bootcamp taught by MIT PhD Dr. Sreedath Panat. It teaches engineers how to build complete voice systems using speech recognition, language models, text-to-speech, tool calling, memory and real-time streaming.

Through eight technical lectures and a capstone project, you’ll progress from a simple voice loop to a deployable, production-style agent.

Benefits and Learning Outcomes

✅ Understand the complete voice-agent architecture

✅ Build speech-to-text pipelines using Whisper models

✅ Generate voice responses with modern TTS systems

✅ Connect LLMs as the agent’s reasoning layer

✅ Implement tool calling and conversational memory

✅ Handle real-time streaming and user interruptions

✅ Design reliable systems with fallbacks and guardrails

✅ Deploy voice agents locally, in browsers and in the cloud

Complete Course Curriculum

Lecture 1: Voice Agents and System Architecture

Understand the ASR–LLM–TTS pipeline, latency, turn-taking and the difference between batch and streaming systems.

Lecture 2: Speech-to-Text Foundations

Build Python transcription pipelines using Whisper, faster-whisper, Distil-Whisper and voice activity detection.

Lecture 3: Text-to-Speech and Voice Output

Compare TTS technologies and create local or API-based speech-generation pipelines.

Lecture 4: LLMs as the Agent’s Brain

Create concise spoken responses, manage conversation history and design voice-agent personalities.

Lecture 5: Tool Use, Memory and Agentic Workflows

Give agents the ability to search, calculate, schedule, remember information and interact with external APIs.

Lecture 6: Real-Time Streaming Voice Agents

Use WebSockets, incremental transcription, streaming TTS, endpoint detection and barge-in handling.

Lecture 7: Production-Grade Architecture

Explore modular system design, retries, logging, safety, model selection, observability and cost optimization.

Lecture 8: End-to-End Voice Agent Project

Build, test and deploy a complete agent such as an AI receptionist, meeting assistant, research assistant or desktop assistant.

Tools and Technologies Covered

The bootcamp uses Python, WebSockets, Whisper, faster-whisper, Distil-Whisper, Piper, Coqui TTS, Silero VAD and LLMs such as Claude or GPT.

Research Starter Kit

The optional Research Starter Kit is designed to accelerate a voice-AI research project with:

• A personalized eight-week research roadmap
• An initial 6–8-page research-paper scaffold
• A curated reading list of 12–15 relevant papers
• A literature-tracking matrix
• A documented starter-code template

Because the official page sells the Research Starter Kit separately and through bundles, confirm that it is included in the version you purchase.

Who Is This Training For?

This program is designed for software engineers, AI developers, researchers and technical builders who want to create voice-powered products or transition into conversational AI engineering.

Although concepts are taught from scratch, the course is technical and uses Python, system architecture and production-engineering workflows.

Start Building Voice AI Systems

Learn how the complete voice-agent pipeline works and develop a practical project that demonstrates your engineering skills.