sequentialign

This is the Python implementation of the 'Sequentialign' algorithm in the AIED 2022 paper "Towards Aligning Slides and Video Snippets: Mitigating Sequence and Content Mismatches" by Ziyuan Liu and Hady W. Lauw.

Implementation Environment

• python == 3.8.8
• numpy==1.20.1
• scipy==1.6.2
• python-pptx==0.6.18

Run

python main.py

Parameter Setting

• -dn: dataset name
• -ev: eval_only: yes=evaluate metrics using cached results, no=run algorithms and overwrite cached results
• -th: filter_threshold: integer(s). indicates thresholds for the sequentialign irrelevant content filter

Data

Each dataset should be placed as a separate subdirectory in the ./data folder. The name of a dataset is the name of the subdirectory in which it is contained. Each slide deck-video pair should occupy a sequentially-numbered subdirectory in the respective dataset directory, containing the following files:

• slides.pptx: a .pptx PowerPoint file containing the deck of slides.
• annotation.txt: a text file containing the duration of the video (in seconds) in its first line, and the start and end times of each slide in the video in subsequent lines.
• transcript.json: a .json file containing the transcript of the video in YouTube format.

A sample is provided in the ./data/sample directory to illustrate this.

Reference

If you use our paper, including the code contained herein, please cite

@inproceedings{sequentialign,
  title={Towards Aligning Slides and Video Snippets: Mitigating Sequence and Content Mismatches},
  author={Ziyuan, Liu and Lauw, Hady W.}, 
  booktitle={The 23rd International Conference on Artificial Intelligence in Education},
  year={2022}
}