Lecture Auto-Transcriber

An automated tool for transcribing lecture recordings from Google Drive using OpenAI Whisper.

Overview

Lecture Auto-Transcriber is designed to convert spoken lecture content from Google Drive into text, making educational materials more accessible and searchable. The tool processes audio/video lecture files and generates accurate transcriptions that can be used for study, reference, or accessibility purposes.

Prerequisites

• Python 3.8 or higher
• FFmpeg

Installation

Installing FFmpeg

FFmpeg is required for processing audio files before transcription.

On Windows:

1. Download the FFmpeg build from the official website or from gyan.dev (recommended for Windows)
2. Extract the ZIP file to a location of your choice (e.g., C:\ffmpeg)
3. Add FFmpeg to your system PATH:
   • Open "Edit the system environment variables" from the Control Panel
   • Click "Environment Variables"
   • Edit the "Path" variable under System variables
   • Add the path to the FFmpeg bin directory (e.g., C:\ffmpeg\bin)
   • Click OK to save changes

On macOS (using Homebrew):

brew install ffmpeg

On Ubuntu/Debian:

sudo apt update
sudo apt install ffmpeg

Installing Lecture Auto-Transcriber

1. Clone this repository:

git clone https://github.com/Vethya/lecture-auto-transcriber.git
cd lecture-auto-transcriber

2. Create and activate a virtual environment:

python -m venv env

On Windows

.\env\Scripts\activate

On macOS/Linux

source env/bin/activate

3. Install dependencies:

pip install -r requirements.txt

4. Set up credentials:

• Create a config.json file with your settings the Google Cloud Console by:

1. Go to the Google Cloud Console
2. Create a new project
3. Enable the Google Drive API
4. Create OAuth credentials (Desktop application)
5. Download the credentials JSON file and rename it to credentials.json

Configuration

Create a config.json file in the root directory with the following structure:

{
  "subjects": {
    "research methodology": {
      "recording_folder_id": "YOUR_RECORDING_FOLDER_ID"
    },
    "mathematics": {
      "recording_folder_id": "YOUR_RECORDING_FOLDER_ID"
    },
    "data science": {
      "recording_folder_id": "YOUR_RECORDING_FOLDER_ID"
    },
    "cloud computing": {
      "recording_folder_id": "YOUR_RECORDING_FOLDER_ID"
    },
    "project development": {
      "recording_folder_id": "YOUR_RECORDING_FOLDER_ID"
    }
  },
  "gemini_api_key": "YOUR_GEMINI_API_KEY",
  "mongodb_uri": "mongodb://localhost:27017",
  "drive_credentials": "credentials.json"
}

Usage

python main.py