Building a Voice-Based Health Education Assistant with React, AWS, and ChatGPT

Imagine a patient speaking into a mobile app and instantly receiving a clear, natural-sounding explanation about their health concern. With advances in speech recognition, natural language processing, and text-to-speech, this is no longer futuristic— we will see a demo of this implementation.

In this post, we’ll explore how to architect and implement a voice AI chatbot for health education that:

1. Listens to a user’s health question.

2. Transcribes it into text.

3. Queries an AI model (ChatGPT) for an answer.

4. Converts the response back into natural speech.

5. Plays it back to the patient.

Why Voice for Health Education?

• Accessibility: Voice removes literacy barriers and makes health information more inclusive.

• Convenience: Patients can interact hands-free.

• Engagement: Natural conversations feel more intuitive than reading long articles.

High-Level Architecture

Here’s the flow of the system:

1. User speaks into a React app.

2. The app streams the audio via Socket.IO to AWS Transcribe.

3. AWS Transcribe converts speech to text and returns it.

4. The transcription is sent to ChatGPT API.

5. ChatGPT generates a patient-friendly answer.

6. The answer text is sent to AWS Polly.

7. Polly generates natural voice audio.

8. The React app plays the audio back to the user.

Demo Video

Note: This architecture is for demo purpose and not for production use.