3.8 / 5

Sign Language Tutor

Camera watches your hands, gives feedback on ASL signs

Serious

Privacy

Instant

Zero Cost

The Problem

Sign language learners can't get feedback on their signing without a tutor

Current Solutions (Not Great)

Expensive tutors, video courses (no feedback), practice with deaf friends (limited availability)

Who Needs This

ASL students, parents of deaf children, interpreters in training, CODA (children of deaf adults)

Learning sign language from videos is hard because you can't get feedback on your own signing. Sign Language Tutor watches your hands through the camera and tells you if you're making the sign correctly—hand shape, movement, position. It's like having a patient deaf instructor available 24/7, and your practice sessions stay completely private.

Honest Take

Meaningful accessibility project with underserved audience. SignAll and similar startups have raised funding for this. Technical challenge is real—ASL recognition is complex and movement-based signs are harder than static ones. Partner with deaf education organizations for curriculum and validation. Grant funding opportunities exist for accessibility tech.

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

Sign recognition with accuracy feedback
Hand shape correction suggestions
Movement and position guidance
Curriculum-based lesson progression
Fingerspelling practice
Common phrases and vocabulary
Side-by-side comparison with reference
Progress tracking by sign mastery

Build Prompt

Use this prompt with an AI assistant to start building

Build a React PWA called 'Sign Language Tutor' using WebInfer and MediaPipe Hands. UI: split view with reference sign video/image on left, user camera on right, feedback panel below. Use getUserMedia() for camera. Run MediaPipe Hands to extract 21 hand landmarks per hand. For lesson mode: show target sign, user attempts, compare hand configuration. Use generateObject to return { signRecognized: string, confidence: number, handShapeCorrect: boolean, movementCorrect: boolean, positionCorrect: boolean, corrections: [{ aspect: string, current: string, target: string, tip: string }], overallScore: number }. Overlay correction arrows on canvas. Fingerspelling mode: random letters, user signs, immediate feedback. Lesson curriculum stored locally. Track mastery percentage per sign in IndexedDB.

Score Breakdown

Pain