WebInfer

3.8 / 5

Stage Sense

Live feedback on pace, filler words, and engagement while presenting

Useful
Real-time

The Problem

Presentation skills are hard to self-assess; feedback usually comes too late to act on

Current Solutions (Not Great)

Practice alone (no feedback), record and review (tedious), coaching (expensive)

Who Needs This

Professionals who present, executives, salespeople, teachers, conference speakers

Practicing presentations alone is ineffective because you can't objectively judge your own delivery. Stage Sense runs alongside your presentation and gives real-time feedback: you're speeding up (slow down indicator), you've said 'basically' five times (word alert), your energy dropped during that slide (bring it back). It's subtle enough to use during real presentations, not just practice. After the presentation, get a detailed breakdown of your delivery patterns.

Honest Take

There are players like Orai and Yoodli here too, but the market isn't saturated. Corporate training budgets are huge and presentation skills are evergreen. The challenge is making the feedback valuable enough that people actually use it beyond one practice session—sticky retention is hard.

Monetization Ideas
Ways to turn this into revenue

Freemium

Free basic, $5-15/mo for pro

Subscription

$5-29/month or $49-199/year

One-Time Purchase

$9-49 per license

Features
Key features that make this app valuable
  • Speaking pace monitoring (WPM)
  • Filler word counting and alerts
  • Pause detection (too few/too many)
  • Energy/vocal variety analysis
  • Slide timing tracking
  • Subtle visual indicators during presentation
  • Post-presentation detailed report
  • Improvement tracking over time
Build Prompt
Use this prompt with an AI assistant to start building
Build a React PWA called 'Stage Sense' using WebInfer and Web Audio API. Two modes: Practice Mode (full feedback) and Live Mode (minimal indicators). Start: getUserMedia for audio. Continuous audio analysis via AudioWorklet: detect speech vs. silence, calculate speaking rate, identify filler words (um, uh, like, basically, you know, so). Use generateObject every 30 seconds to return { speakingRate: number, fillerWords: { word: string, count: number }[], pausePattern: 'too-few'|'good'|'too-many', energyLevel: number, vocalVariety: number, currentIssue?: string }. Practice Mode UI: larger dashboard with real-time metrics, waveform visualization, prominent alerts. Live Mode UI: tiny floating bar (bottom of screen), just colored indicators (green/yellow/red for pace, filler count number, energy dot). Post-presentation: full timeline report with segments scored, specific filler word timestamps, comparison to past presentations. 'Rehearsal' feature: set slide count, target time, get pacing guidance.
Score Breakdown
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