Automatically detect and tag the essential important musical features of your tracks, giving you the rich data needed to curate more cohesive and impactful performances.
Genres and sub-genres in music are ever-changing, overlapping, and often borderless concepts. At Djoid, we’ve spent two years building a Genre Detection model designed to enrich your music library. This frees up your time to add your own custom tags, making your library truly unique to your profile and sound.
Our Approach to Genre Detection
In our Berlin research lab, we spent two years working with music curators, DJs, and music data scientists to identify the key elements and features that define each music genre. Genres are fluid and ever-changing, making it a unique challenge to build a model tailored specifically to the DJ industry. Today, we’re proud to introduce Djoid’s Genre Detection Model—the first of its kind in DJ software—designed to analyze your audio files with remarkable precision.
Our journey included collaboration with artists and curators to capture the essence of genres, engaging with our users to understand their needs, and studying diverse genre categorizations from around the world. By synthesizing these insights, we created a genre detection model uniquely suited for DJs.
Through extensive research and advanced machine learning, we’ve developed a preliminary version of our Main Genre Detection model with an industry-leading accuracy of 87%, setting a new standard for music curation in DJ software.
Djoid’s Genre Detection model sets a new standard for precision and accuracy in music curation. Unlike generic market models that broadly classify “EDM”, “Electronic”, our model captures the nuanced overlaps and defining traits of SPECIFIC genres, ensuring meaningful and reliable tagging.
We deliver an industry-leading 87% accuracy. Designed specifically for the DJ industry, this model provides the rich data you need to focus on curating impactful and creative performances.
Experience how Djoid analyzes the intricacies of your music, detect genres, energies, danceability, emotions with unparalleled accuracy. Each curve and peak contributes to understanding your tracks, giving you precise data for smarter curation.
