Elevator pitches, interviews, selling yourself... whether they be for jobs, internships, or university applications - are an inevitable and stressful part of life. While we could always go through practice questions, it's difficult to evaluate key communication skills such as eye contact, smiling, and talking at a reasonable pace. We decided to make an app that would make the interview prep experience more convenient and help a large sector of the population gain confidence and competence heading into interviews.
The name "ElevAIte" incorporates the concepts of elevator pitches, elevating/improving oneself, and AI/technology.
What it does / How we built it
Challenges we ran into
The biggest challenge was integrating the Python/OpenCV back-end with a web app front-end using Flask, as well as dealing with deadlocks in our multithreaded application. Also, it was difficult improve on tracking eye movements in OpenCV since the pupil is small and the API - not being 100% accurate - would often identify nostrils or background objects as eyes.
Accomplishments that we're proud of
- Not overdosing on caffeine
- Not spilling drinks or getting Cheeto dust on electronics
- Pretty UI for once
What we learned
- Integration is hard (as expected)
- Always git pull before you git push in order to git out of merge errors
- It is possible to function on 4 hours of sleep for the entire weekend
What's next for ElevAIte
This app has great potential for expansion: we could market it to both interviewees and recruiters who conduct webcam interviews because it would be useful to obtain quantitative data about the emotion/tone and personality of the candidates. We were planning to incorporate more text analysis APIs that determined the mood, personality, and overall positivity of a piece of text. We could also add features such as timed practice interview questions for a more realistic environment, or allow users to track their progress in various metrics over time.