AI Interview Coach

AI platform for interview practice that transcribes speech, tracks WPM, detects filler words, and gives real-time feedback to improve confidence and communication skills.

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Inspiration

Many students and job seekers struggle with speaking confidently during interviews, even when they have strong technical knowledge. Most preparation tools focus on theory, not real speaking practice. This project was inspired by the need for a platform that allows users to practice speaking, receive analysis, and improve communication through actionable feedback.

What it does

AI Interview Coach is a real-time speaking practice platform. Users can start a live session where the system listens to their speech, generates a transcript, tracks words per minute, detects filler words, and evaluates confidence levels. The platform then provides AI-powered feedback and suggestions to improve clarity, pacing, and overall communication. After each session, a performance report is generated with insights and recommendations.

How we built it

The application was built using React, TypeScript, Tailwind CSS, and shadcn-ui for the frontend. Speech input is captured using the Browser Web Speech API. Real-time analytics calculate WPM, filler words, and confidence. Gemini AI is used to generate feedback and coaching suggestions. The project follows a live session pipeline connecting transcription, analytics, and AI feedback into one system.

Challenges we ran into

We faced challenges with reliable speech transcription, syncing real-time analytics with feedback, handling browser microphone permissions, and managing API calls without delays. Designing a smooth live session experience and ensuring the system responds quickly was also a key challenge.

Accomplishments that we're proud of

We successfully built a working real-time communication coaching platform. The system can capture speech, generate transcripts, analyze performance metrics, and provide AI-driven feedback. Creating a complete session-to-report workflow is one of the biggest accomplishments of this project.

What we learned

We learned how to integrate speech recognition into web applications, build real-time analytics pipelines, and use AI APIs for feedback generation. We also gained experience in handling live session state, improving performance, and designing user-focused interactive tools.

What's next for AI Interview Coach

Future improvements include more accurate speech analysis, emotion and tone detection, personalized learning paths, multi-language support, and deeper AI coaching insights. The goal is to evolve this into a full communication training platform for interviews, presentations, and public speaking.

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