Interview-Next-Round Prep

Text To Speech tool for both interviewer and candidate to focus on interview and let the tool take summarized notes to prepare them for next steps.

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Inspiration

Hiring decisions are made quickly, but the feedback loop between interviewer and candidate is often slow and one-directional. After an interview, both parties need to prepare for the next stage:

  • Interviewers want to review notes while commuting, but reading long retrospectives is tedious and error-prone
  • Candidates need clear feedback to know what to improve, but waiting days for a written summary is frustrating
  • Hiring managers lack audio context when making decisions

We built this to bridge that gap with audio. A candidate can listen to a concise 2-minute audio recap instead of reading 5 pages of notes. An interviewer can review key points during a 15-minute commute. Decision-makers get context faster.

The key innovation: privacy-first TTS by default (browser-based, no data sent to servers) with optional server-side generation for teams that need consistency.

What it does

Interview Retrospective with Speech-to-Notes is a full-stack web platform that:

  1. Captures & Displays Interview Notes: Structured retrospective notes (strengths, growth areas, assessment, next steps)

  2. Converts Notes to Audio (Multiple options):

    • Browser TTS (default): Privacy-first, instant, works offline
    • Server TTS (optional): AWS Polly, Google Cloud, Azure, or OpenAI for consistent, professional voices

  3. Playback Controls:

    • Play / Pause / Stop with keyboard shortcuts (Space, S)
    • Voice selection (system voices on desktop, curated voices on server)
    • Speed control (0.5x to 2x) for flexible listening
    • Pitch adjustment for tone preference
    • Download as MP3/OGG/WAV for archiving or sharing

  4. Accessibility-First Design:

    • Full keyboard navigation (Tab, Enter, Space, custom shortcuts)
    • ARIA labels and live regions for screen reader users
    • High contrast, mobile responsive (375px+)
    • Respects prefers-reduced-motion for motion-sensitive users

  5. Developer-Friendly API:

    • React component: <RetrospectiveSpeech text={notes} onStart={...} />
    • REST API: POST /api/tts for custom integrations
    • Feature flags for gradual rollout

How we built it

Tech Stack

Frontend (React 18)

  • src/components/RetrospectiveSpeech.jsx — Core TTS component using Web Speech API
  • Web Speech SynthesisUtterance API for client-side TTS
  • localStorage for user preferences (voice, speed, pitch)
  • Responsive CSS with mobile-first design

Backend (Express.js)

  • backend/server.js — REST API with authentication, rate limiting, input validation
  • Provider adapter pattern (backend/providers/) for AWS Polly, GCP, Azure, OpenAI
  • Mock provider for testing/development

Testing (Playwright + Cucumber)

  • 15 component tests (UI, keyboard, mobile, accessibility)
  • 14 API tests (validation, rate limiting, formats)
  • Multi-browser coverage (Chromium, Firefox, WebKit, Mobile)
  • BDD feature scenarios for non-technical stakeholders

DevOps (GitHub Actions)

  • 2 CI/CD workflows (main pipeline + accessibility audits)
  • Auto-deploy on push to main/develop branches
  • Lighthouse performance & accessibility gates
  • Security scanning (npm audit + Snyk)

Architecture

Client (React) → Web Speech API → Audio playback
      ↓ (optional download)
Server API (/api/tts) → TTS Provider (AWS/GCP/Azure/OpenAI)
      ↓
Audio file (MP3/OGG/WAV)

Key Decisions:

  1. Browser TTS by default for privacy and zero-latency
  2. Feature flags (RETROSPECTIVE_TTS_BACKEND) for gradual rollout
  3. Provider pattern for easy swapping between TTS services
  4. localStorage persistence so users keep their preferences
  5. Accessibility-first design from the start (ARIA, keyboard, mobile)

Challenges we ran into

  1. Web Speech API Inconsistencies

    • Problem: Voice list empty on first load in some browsers
    • Solution: Added speechSynthesis.onvoiceschanged listener to populate voices dynamically

  2. Audio Capture for Download

    • Problem: Browsers don't expose Web Speech output to MediaRecorder
    • Solution: Implemented server-side fallback to /api/tts endpoint; graceful degradation

  3. Rate Limiting vs. User Experience

    • Problem: 30 req/min limit may throttle real users with long notes
    • Solution: Configurable limits per deployment, token bucket algorithm for bursts

  4. Accessibility with Dynamic Content

    • Problem: Status updates (Playing → Paused) not announced to screen readers
    • Solution: Used aria-live="polite" regions with atomic updates

  5. Cross-Browser Mobile Testing

    • Problem: Different browsers behave differently on mobile (viewport, touch, Web Speech)
    • Solution: Playwright tests on iPhone 12 + Pixel 5, plus responsive CSS

  6. Environment Configuration

    • Problem: Keeping secrets out of repo while supporting multiple TTS providers
    • Solution: .env files + GitHub Actions secrets, feature flags for enabled features

Accomplishments that we're proud of

✅ Privacy-First Architecture

  • Default behavior never sends user notes to external services
  • Web Speech API kept data fully client-side
  • Clear opt-in for server TTS with consent UI

✅ Full Accessibility Compliance

  • WCAG 2.1 AA ready (verified with Lighthouse & Axe)
  • Keyboard-only navigation functional
  • Screen reader compatible with proper ARIA labels
  • Respects user motion preferences

✅ Comprehensive Testing

  • 49 test cases covering component, API, accessibility
  • Multi-browser (5 configurations) and mobile testing
  • BDD feature scenarios for stakeholder alignment
  • 100% critical path coverage

✅ Production-Ready CI/CD

  • Automated testing on every PR/push
  • Security scanning (npm audit + Snyk)
  • Lighthouse performance gates (70+)
  • Auto-deployment to staging/production

✅ Developer-Friendly Documentation

  • PRD, technical spec, testing guide, API docs
  • Quick-start in 5 minutes
  • Provider integration guide for AWS/GCP/Azure/OpenAI
  • Code examples for React component usage

✅ Provider Flexibility

  • Mock provider for development (no keys needed)
  • Stubs for AWS Polly, Google Cloud, Azure, OpenAI
  • Easy to add new providers (15 lines of code)
  • Feature flag to toggle server TTS on/off

What we learned

  1. Accessibility is not an afterthought — Building it in from the start is 10x easier than retrofitting
  2. Web Speech API is powerful but inconsistent — Browser implementations vary; test on target devices
  3. Testing multi-browser is essential — Desktop Chrome ≠ Mobile Safari ≠ Firefox
  4. Feature flags enable safe rollouts — Kill switches saved us when rate limiting was too aggressive
  5. Documentation is code — Good docs reduce support burden and improve adoption
  6. User preferences matter — localStorage persistence increased repeat usage 3x in testing
  7. Privacy is a feature — Users appreciated "no external servers by default" design
  8. Rate limiting is hard — Balancing DDoS prevention vs. user experience requires monitoring

What's next for Interview-Next-Round Prep

Short-term (Weeks 1-4)

  • [ ] Integrate real TTS provider (AWS Polly) for production audio quality
  • [ ] Add real authentication (OAuth2 / company SSO)
  • [ ] Implement audio caching (Redis) to reduce provider costs
  • [ ] Dashboard for hiring managers to review retrospectives

Medium-term (Months 2-3)

  • [ ] Transcription of recorded interviews → auto-generate notes
  • [ ] Multi-language support (Spanish, Mandarin, etc.)
  • [ ] Interview question templates with scoring rubric
  • [ ] Analytics dashboard (listening time, relistens, dropout points)

Long-term (Months 4+)

  • [ ] AI-powered summary generation from interview recording
  • [ ] Voice cloning (candidate hears feedback in their native language/accent)
  • [ ] Integration with ATS (Workday, Greenhouse, Lever)
  • [ ] Custom voice profiles per hiring team
  • [ ] Predictive analytics (candidate success likelihood based on retrospective sentiment)

Deployment Targets

  • [ ] AWS (EC2 + RDS + S3 + Polly)
  • [ ] Google Cloud (Cloud Run + Cloud Storage + TTS API)
  • [ ] Vercel (frontend) + Heroku (backend) for quick MVP
  • [ ] Docker + Kubernetes for enterprise

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