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A simple script to summarize an mp3 lecture using Openai Whisper for speech recognition and Bart (Facebook model) for summary

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Lectures-zayt

A simple script to summarize an mp3 lecture using Openai Whisper model for audio transcription and the BART model for text summarization . The script transcribes an audio file, generates a summary of the transcription, and saves both the transcription and summary to a Word document.

Requirements

  • Python 3.7 or higher

To install the required libraries, you can run:

pip install -r requirements.txt

Usage

To run the script, use the following command: python app.py <audio_file> [--max_length MAX_LENGTH] [--min_length MIN_LENGTH]

Arguments

audio_file (required): Path to the audio file (e.g., lecture.mp3).

--max_length (optional): The maximum length of the summary. Default is 500.

--min_length (optional): The minimum length of the summary. Default is 200.

Example

python app.py lecture.mp3 --max_length 400 --min_length 150

Notes

  • The script uses default values of 500 for max_length and 200 for min_length if they are not provided.
  • because of the limit of 1024 chunk size the code splits the transcription into 2 parts then do the summarization.

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A simple script to summarize an mp3 lecture using Openai Whisper for speech recognition and Bart (Facebook model) for summary

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