- UX Design
- Product Design
- Logo Design
Verser is an app that will empower users to view song structure, rhyme schemes, and lyrics with deeply-analytical features. The app allows users to analyze existing songs or create their own lyrics, and focuses on improving users' understanding of advanced lyric-writing techniques and the underlying architecture of songs.
Verser is both for song writers and fans or students of music alike. In the last couple years, in-depth song analysis from Genius.com (to annotate the meaning and references behind lyrics) and several popular content creators shows an increased interest in learning and studying the craft of great lyrics. Furthermore, many song writers have to manually create their own grids to plan song structures and often look to the wordplay and approach of famous artists for inspiration.
This project creates several rewarding challenges in designing a robust, unobtrusive, and intuitive user interface and that allows users to focus on analyzing songs. The branding for the app takes inspiration from popular code editors that feature dark themes to further emphasize the lyrics and allow for long sessions of writing and studying. Furthermore, the monospace font allows users to visually see exact character lengths to roughly gauge the duration of each line.
The app provides several layers of functionality that need to look great and not clutter the experience, whether the use has engaged one or all of the features. Initial features include custom syntax highlighting to map sound and rhyme patterns, verse, bars, and line counters, syllable counts, and beat/measure mapping.
I will soon begin initial development for the first prototype of Verser. I plan on using this project to further explore ReactJS, React Native, and document databases to rapidly prototype functionality and interactions.
Future functionality for Verser can move beyond user-generated mapping, and may include machine learning for predictive lyric analysis and integrations with related services such as Genius.com to pair this analysis with semantic annotations and song datbases. However, I am focusing on the core experience of manual content creation features to get the app into the hands of users as quickly as possible.