Sononym is a sample browser that utilizes machine learning to offer new ways of exploring and discovering recorded audio.
The primary innovation in Sononym is audio-based similarity search, which will enable you to find similar-sounding samples in your sample collection based on any source sound you provide. Essentially, a bit like how google’s reverse image search works, but with audio. And, uh, without the ‘internet’ part.
How useful is similarity search?
Read a few testimonials from people who are using Sononym.
The software has been built from the ground up to facilitate similarity search, auto-categorization and classification (tell apart one-shots and loops, or separate kicks from snares) as well as other features that you would expect from a modern sample browser: feature extraction (audio analysis), searchable and sortable file/results views in a streamlined interface.
Our plan is to refine the software based on the feedback we receive, and to bring the Sononym experience to even more platforms.