Case Studies
How We Built a Voice for Millions
Urdu Text-to-Speech System
The Challenge & Our Approach
The Challenge
Visually impaired users lacked access to Urdu-language screen readers
Existing systems weren't equipped to support native language interaction
Created barriers to digital accessibility and independence for blind users
Our Approach
Built a robust Urdu Text-to-Speech model using a custom-curated 100,000-word dataset
Trained with both male and female voices to support contextual and gender-inclusive usage
Seamlessly integrated with NVDA through a one-click plugin for easy accessibility
Solution Architecture & Implementation
Custom Dataset
- 100,000-word custom-curated corpus
- Focused on Urdu language specifics
- Balanced representation of vocabulary
- 100,000 words
Voice Training
- Dual gender voice support (male & female)
- Contextual pronunciation adaptation
- Feedback-driven model tuning
- Continuous Improvement
NVDA Integration
- Seamless one-click plugin installation
- Voice-guided setup process
- Real-world usability designed
- One-click Installation
Measurable Impact & Results
Key Performance Metrics
Real-World Usability
Enabled real-world usability for blind users through voice-guided navigation
Improved daily accessibility
Lowered Barriers
One-click installer significantly lowered the barrier to adoption
Simplified setup process
Voice-Guided Setup
Voice-guided setup experience enhanced user confidence and independence
Intuitive user experience