Healthcare Translation Web App

A web-based prototype for real-time multilingual translation between patients and healthcare providers. This application converts spoken input into text, provides a live transcript, and offers a translated version with audio playback. It leverages OpenAI's GPT-3.5-turbo model for translation and the Web Speech API for speech-to-text and text-to-speech functionality.

Features

• Voice-to-Text: Convert spoken input into a text transcript using the Web Speech API.
• Real-Time Translation: Translate the transcript into multiple languages using OpenAI GPT-3.5-turbo.
• Audio Playback: Listen to the translated text using text-to-speech.
• Mobile-First Design: Responsive and optimized for both mobile and desktop use.

Project Structure

healthcare-translation-app2/

• ├── venv/ # Virtual environment folder
• ├── app.py # Flask backend
• ├── requirements.txt # Python dependencies
• ├── templates/ # HTML templates
• │ └── index.html # Main frontend page
• ├── static/ # Static files (CSS, JS)
• │ ├── styles.css # Custom styles
• │ └── script.js # Frontend logic
• ├── .env # Environment variables (e.g., OpenAI API key)
• ├── .gitignore # Files to ignore in version control
• ├── README.md # Documentation
• └── vercel.json # Vercel deployment configuration

Setup Instructions

Prerequisites

• Python 3.11 or higher
• OpenAI API key (Get it from OpenAI)
• Git (for version control)

Step 1: Clone the Repository

git clone https://github.com/your-username/healthcare-translation-app2.git
cd healthcare-translation-app2

Step 2: Set Up a Virtual Environment

Create a virtual environment:

python -m venv venv
Activate the virtual environment:

On macOS/Linux:

source venv/bin/activate

On Windows:

venv\Scripts\activate

Step 3: Install Dependencies Install the required Python packages:

pip install -r requirements.txt

Step 4: Set Up Environment Variables Create a .env file in the root directory:

OPENAI_API_KEY=your-openai-api-key-here

Replace your-openai-api-key-here with your actual OpenAI API key.

Step 5: Run the Flask App Start the Flask development server:

python app.py

Open your browser and go to:

http://127.0.0.1:5000 Deployment on Vercel Step 1: Install Vercel CLI If you haven't already, install the Vercel CLI:

npm install -g vercel

Step 2: Deploy the App Log in to Vercel:

vercel login Deploy the app:

vercel Follow the prompts to complete the deployment.

Step 3: Set Environment Variables on Vercel Go to your Vercel dashboard.

Navigate to your project’s settings.

Add the OPENAI_API_KEY environment variable with your OpenAI API key.

Usage Open the app in your browser.

Click "Start Speaking" to begin voice input.

Select the target language from the dropdown.

View the original and translated transcripts.

Click "Speak" to listen to the translated text.

Technologies Used Backend: Flask (Python)

Frontend: HTML, CSS, JavaScript

APIs:

OpenAI GPT-3.5-turbo (Translation)

Web Speech API (Speech-to-Text and Text-to-Speech)

Deployment: Vercel

Contributing Contributions are welcome! If you'd like to contribute, please follow these steps:

Fork the repository.

Create a new branch for your feature or bugfix.

Commit your changes.

Submit a pull request.

License This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments OpenAI for providing the GPT-3.5-turbo model.

Flask and Vercel for making deployment seamless.

Web Speech API for enabling speech-to-text and text-to-speech functionality.

Contact For questions or feedback, please reach out to:

GitHub: https://github.com/davidemusi