Skip to content

minciyaks/ai-lecture-notes-generator

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

9 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

🎧 AI Lecture Voice-to-Notes Generator

An intelligent Python + Streamlit application that converts lecture audio into structured study notes including transcript, summary, key points, keywords, important sentences, and a downloadable PDF.

This project is designed to help students quickly convert recorded lectures into clean, readable notes using AI.

📌 This project was developed as part of a 1-month AI/ML Internship program under Edunet Foundation.


🚀 Features

  • 🎙️ Speech-to-Text Transcription using OpenAI Whisper
  • 📝 Automatic Summary Generation
  • 🔑 Key Points Extraction
  • 🏷️ Keyword Detection
  • Important Sentence Highlighting
  • 📄 PDF Export of Notes
  • 🖥️ Clean and simple Streamlit UI

🛠️ Tech Stack

  • Python 3.11
  • Streamlit – Web interface
  • OpenAI Whisper – Speech recognition
  • NLTK – Sentence processing
  • Transformers – Text summarization
  • ReportLab – PDF generation

📁 Project Structure

ai-lecture-notes-generator/
│
├── app.py
├── requirements.txt
│
├── services/
│   ├── __init__.py
│   ├── speech_to_text.py
│   ├── summarizer.py
│   ├── keywords.py
│   ├── sentences.py
│   └── important_sentences.py
│
├── utils/
│   ├── __init__.py
│   ├── file_handler.py
│   └── pdf_generator.py
│
├── audio/
│   └── sample audio files
│
├── lecture_notes.pdf
└── README.md

▶️ How to Run

1. Clone the repository

git clone https://github.com/minciyaks/ai-lecture-notes-generator.git

2. Navigate into the project folder

cd ai-lecture-notes-generator

3. Create and activate virtual environment

python -m venv venv
venv\Scripts\activate

4. Install dependencies

pip install -r requirements.txt

⚠️ FFmpeg must be installed on the system for audio processing.

5. Run the application

streamlit run app.py

📄 Sample Output

A sample generated PDF (lecture_notes.pdf) is included in this repository for demonstration and verification of output quality.


📌 Use Cases

  • Students converting recorded lectures into notes

  • Self-study and exam revision

  • Online course learners

  • Internship / academic project demonstration


👩‍💻 Author

Minciya K S | BCA Student


About

An AI-powered Python & Streamlit app that transforms lecture audio into structured notes, summaries, and downloadable PDFs.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages