I went to the AWS User Group Chennai Meetup on September 27, 2025, and one session really stood out to me. Ilanchezhian Ganesamurthy, who is an AWS Hero, gave a really interesting talk about creating Voice AI Agents using AWS Voice Technology and Amazon Nova Sonic. Since I've always been interested in how AI is making technology more conversational and easier to use, this session provided a lot of useful and practical information.
Let’s be honest, we’ve all had those annoying customer service calls where the AI just doesn’t understand what you’re saying. This session shows how we’re moving away from that and moving toward something more natural and smart.
Understanding Voice AI Agents
Voice agents use the speech and thinking powers of large language models, like the ones behind Alexa or Siri. These agents can talk back and forth in a way that feels real, understanding what you’re saying and even handling interruptions during a conversation.
You might be thinking, why is this important? Picture calling your bank and having a chat that feels like a real conversation. You can stop to ask questions, and the AI listens and adjusts to how you speak. That’s the power of today’s voice agents.
Two Approaches to Building Voice Agents
The traditional approach breaks voice interaction into three distinct steps:
Speech-to-Text (STT): Your voice is turned into text using services like AWS Transcribe, Deepgram, or Azure AI Speech.
Large Language Model (LLM): The text is handled by AI models such as Amazon Bedrock, Google Gemini, or Azure OpenAI to figure out what you mean and create a reply.
Text-to-Speech (TTS): The AI's reply is then changed back into speech using tools like AWS Polly, ElevenLabs, or Azure AI Speech.
The thing is, this method works for a lot of situations, but there's a downside. Each step adds a little delay, so there's a small time gap between when you speak and when you hear the response. In customer service, even a tiny delay can affect how natural the conversation feels.
The setup shown in the session uses Pipecat, which is a framework that helps organize conversational AI parts. It connects users through WebRTC for real-time chats. It also includes Voice Activity Detection to know when someone is talking, Amazon Transcribe for understanding speech, Pipecat Flows to manage the conversation, Amazon Bedrock for thinking through the response, and Amazon Polly to turn text back into speech.
Speech-to-Speech with Amazon Nova Sonic
Amazon Nova Sonic is changing the way things work. Instead of going through three steps, it uses a direct speech-to-speech model that handles the whole conversation without turning speech into text in between.
Does that sound familiar? It's similar to the difference between translating each word of a conversation separately versus truly understanding the whole meaning and responding in a natural way. Nova Sonic does this using a bidirectional streaming API, allowing it to listen and reply at the same time, just like people talk in real life.
The setup is simpler: voice input goes through VAD, then straight to Nova Sonic for processing, with Pipecat handling the conversation’s context and state. This makes the system faster and helps create more natural conversations.
Amazon Nova Sonic: Core Capabilities
Let me break down what makes Nova Sonic special:
Low latency: It allows for live conversations between people where the speech is converted to speech with very little delay.
Multilingual support: It can understand many languages and different ways people speak, making it useful around the world.
Expressive voices: It provides eleven different voice choices in English, Spanish, German, French, and Italian, including both male and female voice options.
Natural dialog handling: What makes it really good is that it can understand and adjust to pauses, stutters, and interruptions in speech while keeping track of the conversation.
Tool integration: It can link to company software and tools, so it can use your business's own information to reply.
Task completion: It helps people answer questions, make bookings, and complete tasks related to their work.
Amazon Nova Model Family
The session also mentioned that Nova Sonic is part of a bigger Amazon Nova family. Let me give you a quick summary:
Nova Micro: Fast, text-only model for lowest latency responses
Nova Lite: Multimodal model that understands text, images, and video, great for quick processing
Nova Pro: Best combination of quality and speed for complex multimodal tasks
Nova Premier: The most capable model for complex tasks and teaching other models on Amazon Bedrock
Nova Canvas: Image generation model
Nova Reel: Video generation model
Nova Sonic: Live speech model for natural voice conversations
Nova Act: Research preview for advanced capabilities
Each model is designed for different purposes, but Nova Sonic focuses on voice interaction.
Real-World Use Cases
To be fair, knowing the technology is one thing, but knowing where to use it is really important. The session showed several real-world uses:
Customer service: First, helping customers with their questions, handling sales requests, or answering insurance-related queries, any situation where you’d usually have a call center agent.
Task automation: Second, making bookings, managing sales processes, and finishing transactions through voice.
Learning and development: Third, helping people improve their skills and doing practice interviews.
Healthcare accessibility: Improving accessibility in medical settings and therapy applications
In short, if your business involves phone interactions or voice-based experiences, voice agents could change how you run your business.
Technical Components
For those who want to know more about the technical part, let me explain some important ideas from the session in a simpler way:
ASR (Automatic Speech Recognition): Also called STT, converts your speech to text
TTS (Text-to-Speech): Also called Speech Synthesis, converts text to spoken words
LLM: The AI brain that understands meaning and generates intelligent responses
VAD (Voice Activity Detection): Detects when humans are speaking in audio, helping the system know when to listen
WebRTC: Real-time communication protocol using UDP for full-duplex, persistent connections, ideal for live voice
WebSocket: TCP-based full-duplex connection designed for streaming audio and video
Knowing these basic parts can help you design better voice-based systems.
Conclusion
Voice AI is changing quickly, and Amazon Nova Sonic is helping make conversations sound more real than ever. It's great for creating customer service chatbots, tools that help people with disabilities, or anyone interested in the future of AI. It's a good idea to try it out if you're working on similar projects.
The AWS User Group Chennai gathering keeps offering useful talks like this one, so if you're nearby, you should consider joining.
About the Author
As an AWS Community Builder, I enjoy sharing the things I've learned through my own experiences and events, and I like to help others on their path. If you found this helpful or have any questions, don't hesitate to get in touch! 🚀
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References
Event: AWS User Group Chennai Meetup
Topic: Voice Agents with Amazon Nova Sonic
Date: September 27, 2025
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