Live speech tracking, with varying levels of memorization, to ensure that users can effectively learn their scripts..
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Provides live feedback to users, allowing them to make real-time adjustments to improve their presentation skills.
Encourages users when they are doing well, further increasing their confidence to speak in front of others.

Speechful: Cal Hacks 12.0

Inspiration

Public speaking can be intimidating, and practicing alone often lacks meaningful feedback. We wanted to create a tool that provides real-time, personalized coaching, helping users improve confidence, clarity, and engagement.

What it does

Speechful is a public speaking coaching app that analyzes your speech in real-time and gives personalized feedback. It evaluates factors like sentiment, confidence, and speech familiarity, helping users refine both content and delivery.

How we built it

Frontend: React + TypeScript for a clean and responsive interface where users can record speeches and see feedback.
Backend: Node.js + Express to handle API requests, process data, and return actionable insights.
Speech Analysis:
- Claude API and Lava API for sentiment analysis, scoring the speaker’s confidence and engagement.
- Voice detection AI APIs to track how well the user is familiar with their speech (intonation, pauses, and fluency).
Live Feedback: Combines the above metrics to provide personalized advice on pacing, clarity, and emotional impact.

Challenges we ran into

Integrating multiple AI APIs and ensuring their outputs were consistent and interpretable.
Real-time processing: delivering feedback without noticeable lag.
Designing actionable feedback, presenting insights in a way that’s easy for users to act on without overwhelming them.

Accomplishments that we're proud of

Successfully integrated Claude and Lava APIs for sentiment scoring and personalized feedback.
Built a working prototype that tracks speech familiarity and provides actionable coaching.
Designed a real-time dashboard that gives intuitive, immediate insights during practice sessions.

What we learned

Combining multiple AI APIs can create rich, multidimensional feedback for users.
Real-time processing requires careful optimization to maintain responsiveness.
Personalized feedback is far more effective than generic tips as users respond better when advice is tailored to their own performance.

What's next for Speechful

Add tone and emotion detection to give more nuanced feedback.
Introduce progress tracking over multiple sessions to help users see improvement over time.
Expand multilingual support for non-English speakers.
Build a mobile version for on-the-go practice.