Building an AI Voice Assistant Using AWS Serverless and Bedrock Nova

#aws #cloud #novamicro #serverless

General Context

The growing interest in natural language interfaces has made voice assistants more relevant than ever. With the rise of tools like Amazon Bedrock and the introduction of generative voices in Amazon Polly, it’s now possible to create sophisticated voice applications using entirely serverless infrastructure.

In this article, I’ll walk you through the architecture and implementation of an AI voice assistant that listens to your voice, transcribes your question, uses a generative model to understand and respond, and finally speaks the answer back to you. The whole solution is built using AWS serverless services, making it scalable, cost-effective, and easy to deploy.

You can find the complete project repository on GitHub.

Deep Dive on AWS Resources

To create this voice assistant, I used a combination of AWS services that seamlessly interact:

Amazon S3:

Stores the audio files and acts as the glue for processing. It temporarily holds the user's recorded voice (WebM format) and also the synthesized audio response.

Amazon Transcribe:

Transcribes the uploaded audio into text using its real-time transcription API. It supports various languages and accents, and it integrates well with other AWS services in the workflow.

Amazon Bedrock (Nova Micro):

This is the brain of the application. The transcribed text is sent to a foundation model hosted on Amazon Bedrock—in this case, Nova Micro. It generates a coherent and human-like response based on the user’s input.

Amazon Polly (Generative Voice):

Once the response text is generated, Amazon Polly converts it into audio using one of the new generative voices, delivering a more natural, expressive tone compared to traditional TTS.

AWS Lambda:

Orchestrates the entire process:

Triggered by S3 uploads
Calls Amazon Transcribe and waits for transcription
Sends prompt to Bedrock and receives the response
Converts response text to speech with Polly
Returns a signed URL to the audio for playback

Amazon API Gateway:

Exposes the backend as a secure REST API. It allows the front-end to send the user’s voice and receive the audio response.

Deep Dive on Application

The front-end is a simple JavaScript application that records the user’s voice via the browser, sends it to the backend, and plays the response. It includes:

Audio recording using MediaRecorder
File upload to an S3 presigned URL
Asynchronous polling until the processed voice response is ready
Playback of Polly's generative voice output

The back-end architecture follows an event-driven pattern:

User speaks a question.
Audio is uploaded to S3.
Lambda is triggered on object creation.
Audio is transcribed using Amazon Transcribe.
Text is sent to Bedrock Nova Micro for a response.
The response is synthesized into speech using Amazon Polly generative voices.
A signed URL is returned to the front-end.

All services are defined in infrastructure-as-code via the AWS Serverless Framework, making the deployment repeatable and easy to manage.

Cost Estimate

Here’s a rough cost estimate based on moderate usage (100 requests/day):

Amazon S3 | 1 GB storage, 5K PUT/GET | ~$0,14
Amazon Transcribe | 10 hours/month | ~$0,24
Amazon Bedrock (Nova Micro) | 500K input/output tokens | ~$0,09
Amazon Polly (Generative) | 10 hours of audio | ~$0,00
Lambda (1M requests + 5000 ms + 128 MB) | ~$3.00
API Gateway | 1M calls/month | ~$3.50

💡 Total Estimated Monthly Cost: ~$9,56

You can tweak your usage and run your own estimate using the AWS Pricing Calculator.

Final Considerations

This project showcases how powerful AWS serverless technologies can be when building modern, AI-powered voice interfaces. By leveraging Amazon Polly's new generative voices, Bedrock’s advanced language models, and an event-driven architecture, you can create a seamless voice assistant with very low overhead.

The best part? It scales effortlessly—whether you're running one or 10,000 daily conversations.

I encourage you to explore the GitHub repo, fork it, and make it your own. You can easily swap out the voice model, add authentication with Cognito, or even extend it to support multi-turn conversations.

Feel free to leave questions or feedback in the comments!