Inspiration One of the prompts given to us had to do with helping groups of students have more accessibility to university material. Using NLP and machine learning, there was a great opportunity to help students have better access to their lectures.
What it does When uploading a lecture video, it generates transcriptions of the lectures in any desired language.
How it works UI, Database, Backend
How we built it [Alphabetical Order] Daniel: API [Figure how to translate to different languages], Database [Firestore], Heidy: Database [Firestore], JT: Frontend written in JavaScript, using React framework and JSX, Rickey: Figure how to receive video files via upload endpoint, Frontend, and FLASK server to connect Frontend with backend
Challenges we ran into Overall, the connectivity was the biggest issue. We all worked pretty hard trying to figure out why our files weren't being updated correctly, but we weren't able to figure it out in the end.
Accomplishments that we're proud of This was our very first project outside of class, so we were proud of getting super close to completing it. The connectivity piece was the only thing we missed really, and I am sure with more time and help we would've been able to get it working.
What we learned Throughout this decal, we learned several things, but putting it into a project, made us see how it all comes together. For most of us, it was our very first project outside of the classroom, so it was interesting to see how all of our parts of the project were able to come together.
What's next We would like to complete it, then figure how to add more data and be able to bring up previous lectures you've translated already.
Built With
- firebase
- gcloud
- javascript
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