Inspiration
Many students and job seekers struggle with speaking confidently during interviews. Most preparation tools focus on theory, not real speaking practice.
This project was inspired by the need for a platform that allows users to actually speak, get analyzed, and receive actionable feedback on their communication.
What it does
This is an AI-powered interview practice and communication improvement platform.
Users can start a live session where the system:
- Listens to speech in real time
- Generates a transcript
- Tracks words per minute (WPM)
- Detects filler words like “um” and “uh”
- Calculates a confidence score
The platform then uses AI to provide personalized feedback to improve clarity, pacing, and delivery.
After each session, a report is generated with insights and improvement suggestions.
How I built it
- Frontend built using React, TypeScript, Tailwind CSS
- UI components using shadcn-ui
- Speech captured using Browser Web Speech API
- Real-time analytics for WPM, filler detection, and confidence scoring
- AI feedback powered by Gemini API
- Session handling and live pipeline architecture for transcript → analytics → feedback
Challenges I ran into
- Handling real-time speech transcription reliably
- Syncing transcript, analytics, and AI feedback together
- Managing microphone permissions and browser limitations
- Preventing feedback delays and API overload
- Designing a smooth live-session experience
What I learned
- Integrating speech recognition into web applications
- Building real-time analytics pipelines
- Using AI APIs for feedback and coaching
- Managing live session state and performance
- Improving UX for interactive AI tools
Accomplishments that I'm proud of
- Built a working real-time speaking practice platform
- Implemented live transcript + analytics pipeline
- Integrated AI coaching feedback into the session flow
- Designed a full session → report workflow
Built With
- api
- css
- gemini
- react
- shadcn-ui
- speech
- tailwind
- typescript
- web
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