Transcript Parser

Inspiration

We were inspired to create this project since we realized how difficult it is for students to sit down and watch an hour lecture in one sitting, since we have experienced this multiple times. This inspired us to create a web application that cuts up a long Zoom lecture into smaller videos since we believe it will make remote learning easier as well as increase student retention rates.

What it does

The Transcript Parser takes in an input of a Zoom video and the transcript for the video. Then the program will use natural language processing to scan the transcript and split the video when a specific ending word is said (for our demo, we used the word dainty). With this, the program will return back the Zoom lecture split up into smaller videos according to the professor.

How we built it

This web application was built using

Frameworks and Languages:
- React (HTML and JavaScript)
- Flask (Python)
Libraries:
- Natural Language Toolkit
- Bootstrap
- pymongo
- Requests
- BeautifulSoup4
- Moviepy
Database:
- MongoDB

Challenges we ran into

Some challenges that we ran into with this project were trying to learn flask since none of our members were experienced with it. Also, we ran into an issue where we had spent extra time writing code in order to parse the transcript that was not needed in the end.

Accomplishments that we're proud of

Accomplishments that we're proud of are that we learned how to implement Flask as a backend. As well as using HTTP in our web application.

What we learned

From this project, some of our members learned about backend development and we all learned how to use flask.

What's next for Transcript Parser

For the Transcript Parser, we plan on deploying the web application using Heroku as well as add features to this program that we believe will help remote learning.