Tablab addresses a need for a free, accessible, and responsive guitar tablature editor. Students, educators, hobbyists, and professionals all need some form of tablature to compose and transcribe music. However, traditional tablature creation relies on expensive desktop software like Guitar Pro or editing tabs in plain-text. The success of this project depended on considering data structure design, responsiveness in rendering musical notation, and accessibility.
The most challenging aspect was designing data structures capable of representing the multi-dimensional nature of guitar tablature. Whereas sheet music primarily includes timing and pitch information, tablature displays fret positions, playing techniques, and how chords are voiced across the strings. I structured the data with these considerations in mind and managed them in a React context in the front end. A PostgreSQL schema stores and retrieves front-end’s tab data. Authentication and security follow industry best practices with JWT-based sessions, Passport.js integration, proper password hashing, and accessible form validation.
Designing a responsive and intuitive UI while anticipating the UX that guitarists would expect was a core concern of the project. In addition to React, I used a creative CSS Grid and pseudoclass solution that presents tablature exactly as guitarists would expect to see it on paper, adapts fluidly to different screen sizes, and remains interactive. Moreover, guitarists with visual impairments are poorly served by existing tablature editors. Plain-text tablature is especially problematic for screen readres, which read line by line (i.e., string by string) rather than left-to-right for all strings at once, which is how guitarists read tablature. I implemented semantic markup and ARIA labels to ensure screen readers can meaningfully navigate and interact with the editor and tablature.
Demo Access
To explore the full functionality, use these test credentials:
- Username: `testsandbox`
- Password: `Test1234!`Note: This is a demo environment with sample data.