We want to use the power of automation and Artificial Intelligence to affect any field possible. Job Interviews should not be an exception.

What it does

We have an interviewer and a candidate for a technical job. We can translate speech to text, and then analyze the quality of answers by using Machine Learning algorithms and mark them based on their performance. In addition, we analyze their facial expressions in general to determine their personalities and whether they're fit for company's culture.

How we built it

  • The app is built with RoR.
  • We have used firebase to create a collaboration tool for the interviewer - and the candidate.
  • We have used WebRtc with Peerjs to create a real time video - conference.
  • We have used Google's Web Speech API to translate audio to text and keep - the interview process as records and have access to analyzing each - candidate's answers.

Challenges we ran into

WebRtc not working well.

Accomplishments that we're proud of

Disabling one browser extension, and this solving most of our problems.

What we learned

How to use several APIs to meet our app's specification.

What's next for TalentScale

What's next for htn2015

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