Introduction

This project is designed to speed up lectures by modifying the playback speed based on sound characteristics.

This script is inspired by the work presented in the paper “Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward”. The original Theano implementation can be found here.

The “SpeedLecture” project works by leveraging a Python script, lecture_shortener.py, to intelligently shorten lecture videos based on sound characteristics. Here is an overview of how the project works:

  1. Input Video: The script takes an input video file (INFILE) representing a lecture or presentation.

  2. Output Video: It produces an output video file (OUTFILE) that is a shortened version of the input lecture.

  3. Sound Analysis: The script analyzes the audio characteristics of the lecture video, distinguishing between sound and silence periods.

  4. Dynamic Speed Adjustment:
    • During Sound: The general video speed (SPEED_SOUND) is applied during periods of sound, ensuring that the actual content is presented at a faster pace.
    • During Silence: A different video speed (SPEED_SILENCE) is applied during periods of silence, allowing for faster navigation through less informative segments.
  5. Silence Detection:
    • The script identifies and labels sections as “silent” if the duration of silence exceeds a specified threshold (MIN_SILENCE_LEN).
    • Frames are considered “silent” if their volume falls below a defined threshold (SILENCE_THRESHOLD).
  6. Adjustable Parameters:
    • Users can fine-tune the behavior of the script through various parameters such as the general video speed, silence video speed, minimum silence length, silence threshold, step duration, and the number of processing threads.

  7. Multithreading Support: The script supports parallel processing with multiple threads (THREADS), potentially speeding up the execution time for large videos.

  8. Verbose Output: Users can opt for verbose output, providing additional information during the execution of the script.

By dynamically adjusting the video speed based on sound characteristics, the “SpeedLecture” project aims to provide a more time-efficient way of consuming lecture content, skipping through less informative periods while maintaining comprehension during periods of speech or sound.