MyInterviewer

Inspiration

Practice makes perfect. That's what we've all been told since we were children. Interviews can be stressful and practice is very important. But for some people (CS majors), they have no friends to practice with. But don't stress, we've got you covered. This online web application is built specifically to improve all the minor kinks and details in your interview skills, ranging from technical questions to more broad, general questions. Quick and resourceful feedback leaves you confident for that next interview with Google. Maybe you'll make some friends there!

What it does

This web application initially greets you and prompts you to enter your name for a personalized experience. The link on the page will lead you to a page that will now prompt you to listen to a hard-coded interview question. Recording your response will allow the app to run a series of criteria that will provide feedback to you on how to improve your response (theoretically). Two more interview questions are asked and provide feedback, and then a thank you page is displayed.

How I built it

Work was divided between front-end and back-end On the back-end we developed a server using Flask, processed user voice input using google-speech-to-text-API from google-cloud as well as converting the interview question dataset to speech using google-text-to-speech-API. At this moment only three questions are asked, but this can be easily increased and is simplified for demonstration.

Challenges I ran into

Learning how relevant tools like React work in a short period of time
Integrating the feedback module into the back-end
Learning how it all comes together

Accomplishments that I'm proud of

Sebestien & Muhammad

Activating Google Cloud APIs

Maria

UI and Framework

Naz

Integrating front-end with back-end

What I learned

Sebestien & Muhammad

google cloud and apis
node.js basics
file directory system
git version control
python and javascript

Maria

html and css
React
javascript

Naz

React
google-cloud-api

What's next for MyInterviewer

Implementing a video based input that will detect eye-contact to influence the feedback.
UI improvements
Additional questions with multiple language integration
Replacing dataset of questions with AI created with neural network