NLP Speech Recognition and Translation Project

Welcome to the NLP Speech Recognition and Translation Project! 🌍🔊

In today's globalized world, effective communication across different languages is more important than ever. Our project addresses this need by providing a seamless and intuitive solution for real-time speech translation and text-to-speech conversion. Whether you're traveling, working with international teams, or learning a new language, our application is designed to make language barriers a thing of the past.

Access the hosted project

Hosted Speech Translator Website

Table of Contents

• Features
• Technologies Used
• Project Structure
• Installation
• Usage
• Configuration
• Contributing
• License
• Contact

Features

• Speech to Text Translation 🎤➡️📝: Speak in your native language, and watch as your words are translated into text in another language in real-time.
• Text to Speech Conversion 📝➡️🔊: Convert written text into natural-sounding speech in both the source and target languages.
• Manual Text Input 🖊️: Double-click on the editor to manually enter text if you prefer typing over speaking.
• Copy Text Functionality 📋: Easily copy the translated text with a single click.
• User-Friendly Interface 🖥️: Our application features a clean and intuitive UI built with Chakra UI, ensuring a smooth user experience.

Technologies Used

Frontend

• Next.js: A React framework for server-side rendering and static site generation.
• React: A JavaScript library for building user interfaces.
• Chakra UI: A simple, modular, and accessible component library that gives you the building blocks to build React applications.

Backend

• FastAPI: A modern, fast (high-performance) web framework for building APIs with Python.
• Google Translator: Library for translating text.
• gTTS (Google Text-to-Speech): A Python library and CLI tool to interface with Google Translate’s text-to-speech API.

Containerization

• Docker: Containerization platform to package applications and their dependencies.

Project Structure

.
├── backend
│   ├── Dockerfile
│   ├── app.py
│   ├── requirements.txt
├── frontend
│   ├── Dockerfile
│   ├── package.json
│   ├── public
│   ├── app
│   │   ├── api
│   │   ├── pages
|   ├── components
├── docker-compose.yml

Installation

Prerequisites

• Docker: Make sure Docker is installed and running on your machine.
• Node.js: Node 18+ is required if running the frontend manually.

Running with Docker

1. Clone the repository:

   git clone https://github.com/Aditya-Mishra799/NLP-Speech-Translator-Website.git
   cd NLP-Speech-Translator-Website

2. Build and start the containers:

   docker-compose up --build -d

3. Access the application:

   • Frontend: http://localhost:3000
   • Backend: http://localhost:8000

Running Manually (skip if using Docker)

Backend

1. Navigate to the backend directory:

   cd backend

2. Install dependencies:

   pip install -r requirements.txt

3. Start the backend server:

   uvicorn app:app --host 0.0.0.0 --port 8000

Frontend

1. Navigate to the frontend directory:

   cd frontend

2. Add a .env.local file in the root (frontend).

3. In the .env.local file, add the following environment variable for the frontend to access the backend API:

   # Or you may add the IP at which the Python backend is running here
   NEXT_PUBLIC_TRANSLATOR_API_URL=http://localhost:8000

4. Install dependencies:

   npm install

5. Start the frontend server:

   npm run dev

6. Access the frontend:

   • Frontend: http://localhost:3000

Usage

• Speak to Translate: Click the microphone icon to start speaking. The spoken words will be translated into text in the target language.
• Text to Speech: Click the speaker icon to convert text to speech in the selected language.
• Manual Text Input: Double-click the editor to enter text manually.
• Copy Text: Use the copy button to copy translated text.

Configuration

Environment Variables

The docker-compose.yml file includes environment variables for the frontend service. These variables are set to interact with the backend service running at http://172.17.0.1:8000.

environment:
  - NEXT_PUBLIC_TRANSLATOR_API_URL=http://172.17.0.1:8000

You can modify these values based on your setup.

CORS Configuration

The app.py file in the backend specifies allowed origins for CORS. By default, it includes:

origins = [
    "http://localhost:3000",
    "http://172.17.0.1:3000",
]

Add or modify origins as needed.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Commit your changes (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature-branch).
5. Open a pull request.

License

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

Contact

Developed by Aditya Mishra. For any inquiries, please contact me via adityamishra9124@gmail.com.

LinkedIn: Aditya Mishra

LeetCode: Aditya Mishra

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Thank you for using the NLP Speech Recognition and Translation Project! We hope you find it helpful and easy to use.