InterviewPrep

Practice common Interview Questions and improvise it with our personal recommendation system, curated just for you !

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Inspiration

In these harsh times of recession, there are mass layoffs almost every where, especially in the IT sector. Many people are looking for new opportunities including the new grads and many posses the right tech skills for Software Development. But they lack interview skills and are thus not able to get new job opportunities. So we decided to solve this problem and create a platform where people can practice interview questions for various categories and we give them personalised insights based on their answers.

What it does

Interview Questions

1) The user can choose from multiple sections like General Interview Questions , Software Engineering Interview Questions and see the sample answers and prepare his/her answer accordingly.

Answer Speech Recognition and Analysis

2) After that the user can record his/her answer on our applications which will give personalised feedback to the user like the words per minute the user is speaking, filler words and phrases the user should avoid in the answer, etc.

Named Entity Recognition using NLP Model

3) The application also runs a Natural Language Processing Model for Named Entity Detection to suggest users which user profiles he/she could have added in the answer and what should be excluded.

How we built it

We built the frontend using React which consists of Question categories and respective questions with sample answers for each of them and the backend has been built using Django and Django Rest Framework and it accepts the audio transcript as one of the parameters and then runs the Natural Processing Model we have built and generated personalised recommendations for the user. We also used ngrok to deploy API.

Challenges we ran into

The main challenges we ran into was the task of speech recognition and then building a NLP model for it to process it and do the named entity recognition for the user answer. We overcame this challenge by learning more about NLP models using spacy for named entity recognition.

Accomplishments that we're proud of

We are proud that using this project we have attempted to solve a real world problem that many candidates face while applying for jobs and that is interview rejections. And in these times of recession and mass layoffs, this is surely a tool that will help many to prepare well for interview questions before hand and be confident while appearing for interviews.

What we learned

We learned lot of new things about building applications in Django using DRF and in React as well and learnt to solve errors related to sqlite Database migrations in Django. We also learned about using ngrok for deploying applications from local PC and not a remote computer.

What's next for InterviewPrep

The next step we aim to integrate along with this project is that the recruiter can create virtual interviews and assign to candidates and create a NLP model to process the answers and based on the parameters set by recruiter, judge the candidate's answers and make the recruiter's work easy.

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