Afrolingo is an AI-powered language platform I am building to help users translate and learn African languages using generative models. It currently focuses on the backend logic and AI integration that generates context-aware translations
# Afrolingo – AI Language Platform Prototype
Afrolingo is an AI-powered translation project designed to help users translate and learn African languages using deep learning.
It uses a TensorFlow sequence model trained on paired text data to translate between African languages and English.
## 🧠 Overview
The project explores how artificial intelligence can preserve and promote African languages through intelligent translation models.
It uses a **Flask API** for handling translation requests and a **TensorFlow LSTM model** for language generation.
Although the current version does not include a frontend interface, the backend logic is fully functional and demonstrates the AI workflow.
## ⚙️ Tech Stack
- **Python**
- **Flask**
- **TensorFlow / Keras**
- **scikit-learn**
- **NumPy & Pandas**
## 🚀 How to Run
1. Clone the repository:
```bash
git clone
github.com
cd Afrolingo
📝Install dependencies:
pip install flask tensorflow scikit-learn pandas numpy
Run the Flask app:
python app.py
Test the translation endpoint:
Send a POST request to
localhost with JSON data:
{
"text": "Ndewo",
"source": "Igbo",
"target": "English"
}
📚 How It Works
The train_model.py script loads a dataset of paired African and English sentences.
Text data is tokenized and converted into padded sequences.
A TensorFlow LSTM model is trained to predict the English translation.
The Flask app loads the trained model and tokenizer, accepts user text, and returns AI-generated translations.
🌍 Future Plans
Add a user interface for text input and translation display.
Expand the dataset to cover more African languages.
Integrate a multilingual transformer model (e.g., mBART or MarianMT).
Deploy the API to the cloud (Render, Hugging Face, or AWS).
👩💻 Author
Chidera Okeke Ejiroghene
GitHub: @princess-21
Medium: @wrlegacy21