LanguageLearner

An interactive language learning application that uses AI to help users learn German vocabulary with contextual examples and speech.

Overview

LanguageLearner is a tool designed to facilitate language learning by providing:

• Vocabulary words with translations and explanations
• Contextual example sentences
• Text-to-speech pronunciation in both the target language and English
• Spaced repetition learning algorithm

The application uses a language model to generate explanations and example sentences for German vocabulary words, helping users understand usage in context.

Features

• AI-powered explanations and contextual examples
• Text-to-speech functionality for pronunciation practice
• Visual display of learning content
• Adaptive learning system that focuses on words needing more practice
• Support for A1, A2, and B1 level German vocabulary

Project Structure

LanguageLearner/
│
├── data/               # Language vocabulary data
│   └── deutsch.py      # German vocabulary words
│
├── src/                # Source code
│   ├── prompts.py      # Prompt templates for the language model
│   └── tts.py          # Text-to-speech functionality
│
├── main.py             # Main application file
├── README.md           # Documentation
└── requirements.txt    # Dependencies

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/LanguageLearner.git
   cd LanguageLearner
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

3. Add your language model path in main.py:

   model_path_token = "path/to/your/model"

Usage

Run the application from the root directory:

python main.py

The application will:

1. Select a German word based on the learning algorithm
2. Generate an explanation and example sentences
3. Display the content in a window
4. Read the content aloud
5. Wait for 2 minutes before showing the next word

How It Works

1. Word Selection: Words are selected based on a weighting system. Initially, all words have equal weight. After a word is shown, its weight is reduced, making it less likely to appear soon.

2. Content Generation: The application sends the selected word to a language model, which generates an explanation and contextual examples.

3. Visual Display: The content is displayed in a window with the word, translation, explanation, and example sentences.

4. Text-to-Speech: The application reads the content aloud, alternating between German and English.

5. Progress Tracking: The application tracks progress through a weights file, ensuring focus on words that need more practice.

Customization

• Add new vocabulary words in data/deutsch.py
• Adjust the delay between words by modifying the time.sleep() value in main.py
• Change the voice settings in src/tts.py

License

This project is licensed under the Apache License, Version 2.0 - see the LICENSE file for details.

Citation

@software{LanguageLearner,
  author = {Unsal Gokdag},
  title = {LanguageLearner: AI-Powered Language Learning Tool},
  year = {2025},
  url = {https://github.com/AutomaticHourglass/LanguageLearner}
}