Developing a Subscription-Based Web App for Voice Training and Analysis
Estill Voiceprint
The Challenge
Estill Voice International needed a sophisticated web application that could deliver real-time voice analysis and structured training exercises for vocalists, public speakers, and educators. The goal was to create an intuitive, subscription-based platform accessible from any modern device or browser—one that would provide users with detailed visual and quantitative feedback on vocal performance.
The project required not only a user-friendly interface but also the integration of complex audio signal processing capable of handling real-time analysis across a wide range of devices and environments.
The Solution
Lava designed and developed a cross-platform web application with advanced voice analysis features and guided training modules. Key features included:
A rich, interactive spectrogram and resonance plots for real-time voice visualization
Pitch detection and contour plotting, along with loudness and brightness tracking
A structured voice training and assessment system that allows users to complete exercises and save results for progress tracking
Secure subscription-based access with account management and subscription tiering
To ensure smooth performance across browsers and devices, the system combined a ReactJS front end with a high-performance audio analysis engine built in Rust and compiled to WebAssembly (WASM). A Python-based API backend and PostgreSQL database supported exam tracking and user management.
The Outcome
Though not yet officially launched, early testing and pilot demonstrations of the Estill Voiceprint app have received overwhelmingly positive feedback. The platform is positioned for future subscription growth and is set to meet the growing demand for accessible, data-driven voice training tools.
What Made It Complex
The project’s complexity stemmed from the need to convert theoretical audio processing models into efficient, real-time web applications while ensuring consistent performance across diverse devices and environments. Lava implemented cutting-edge WebAssembly technology for real-time processing and built robust noise resilience and normalization features to adapt to variations in hardware quality and background noise.
