Inspiration
Inspired by the Fall season and the increased pressures faced by students and upcoming grads during job application and early recruitment periods, we sought to create a service specifically designed to assist students who lack access to adequate interview preparation resources. Our system is engineered to deliver a personalized experience to each user, enhancing their interview skills through simulated interviews. Utilizing a sophisticated algorithm and artificial intelligence, AbilityBoost evaluates a student's performance to recommend areas for improvement and to present further challenges with increasingly difficult questions. Additionally, our dedication to inclusivity is reflected in our efforts to accommodate individuals with disabilities, ensuring our service is adaptable to meet the diverse needs of all users.
What it does:
AbilityBoost, a web application, offers personalized live mock interviews tailored to the job description chosen by the user. These interview sessions are recorded, focusing on evaluating nonverbal cues such as body language, eye contact, and eye movements to enhance nonverbal communication skills. To ensure inclusivity and accommodate individuals with diverse disabilities, we initiate a preliminary discussion. During this phase, our AI system identifies and gathers information on any specific needs or adjustments needed. This data acts as a reference for tailoring accommodations during the actual interview process, enabling AbilityBoost to provide effective feedback on users' communication and behavioural skills during the interview when they are more likely to have higher nerves and stress compared to their baseline established in the preliminary chat.
Our interviews cover a spectrum of questions focusing on problem-solving, behavioural insights, and communication skills. Post-interview, users are provided with detailed scores across each category, alongside an aggregated overall score. To support continuous improvement, our system features a "Fast Track" option. When practicing for the same job description again, the system prioritizes areas previously identified as weaknesses, thereby aiding in the enhancement of the user's overall interview performance. Our platform is designed to be user-friendly, featuring a progression graph on the main dashboard, enabling users to monitor their improvement trajectory over time.
How we built it
Our website was developed utilizing a diverse array of technologies. The frontend was constructed using React, incorporating JavaScript and SCSS for dynamic and stylized user interfaces. To process and analyze user's verbal responses, we integrated the Google Speech API. The backend infrastructure is powered by Flask, ensuring a robust and scalable application framework. Additionally, to generate interview questions tailored to specific job types and descriptions, we employed the GPT API, enabling a customized and relevant interview preparation experience for our users.
Challenges we ran into
During the development process, we encountered several challenges, particularly in constructing the generative AI component. Our team found it difficult to locate an online API that fully aligned with our project requirements. Additionally, we faced obstacles in parsing user responses, attributed to complications encountered while sending audio data through the Google Speech API.
Accomplishments that we're proud of
We are proud of being able to develop and offer a solution to a universal challenge that impacts all students each year. Moreover, from a technical standpoint, our team is particularly proud of successfully integrating various technologies into our web application framework, such as Google Speech API, GPT API, Docker, React, and Flask.
What we learned
During our participation in Ellehack, we have gained valuable insights into AI and its practical applications. Furthermore, we dedicated time to understanding the challenges related to online accessibility that many individuals face.
What's next for AbilityBoost: AI-Enabled Interview Practice for All,
Moving forward, our primary objective is to expand the reach of our platform to include a wider array of fields and interview types, such as those in medicine, media, and business sectors. This expansion aims to support students in their preparation for specialized interviews, including those for medical school admissions and professional opportunities beyond. In addition, we plan to enrich the AI's database with an increased volume of data to enhance the user experience, particularly in refining the questionnaire and answer evaluation system. Moreover, with a commitment to inclusivity, we intend to integrate multilingual support into our platform. This development will facilitate global accessibility, allowing users from various linguistic backgrounds to benefit from our service, thereby addressing and overcoming language barriers.
Log in or sign up for Devpost to join the conversation.