Developing a seamless cross-platform solution (Web & Mobile) to convert text into natural-sounding speech, enhancing digital accessibility for global users.
Lead Full Stack Developer
6 Months
4 Developers, 1 Designer, 1 PM
In an increasingly digital world, content accessibility remains a significant barrier. Over 2.2 billion people globally suffer from vision impairment, and millions more face literacy challenges. Traditional Text-to-Speech (TTS) solutions have historically sounded robotic and emotionless, failing to engage users. Furthermore, content creators faced high costs and long turnaround times for professional human voiceovers, limiting the volume of audio content available.
Lyzerslab engineered Speaknix, a state-of-the-art AI voice synthesis platform. We leveraged advanced Deep Learning models (Tacotron 2 and WaveGlow) to produce human-like speech with variable intonation and emotion. The platform offers an intuitive dashboard for content creators to generate audio in real-time and an API for developers to integrate voice capabilities into their apps. We prioritized low-latency inference to ensure instant feedback and a smooth user experience.
Analyzed existing TTS limitations and interviewed 50+ visually impaired users to understand pain points.
Curated 500 hours of high-quality voice data to fine-tune Tacotron 2 and WaveGlow models for natural intonation.
Built a scalable microservices architecture using FastAPI for inference and Next.js for the frontend dashboard.
Conducted A/B testing with human listeners to optimize MOS (Mean Opinion Score) and reduce latency.
Content Creators, Educational Institutions, Accessibility-Focused Enterprises
We plan to introduce real-time voice cloning for personalized branding and expand language support to 100+ dialects by Q4 2024.