Sononym is a sample browser that utilizes machine learning to offer new ways of exploring and discovering recorded audio. Our aim is to make sample search smart, powerful and fun.
The primary innovation in Sononym is something called “similarity search”, which enable users to find similar-sounding samples in their sample collection based on any source sound. Essentially, a bit like how google’s reverse image search works, but with audio.
The software has been built from the ground up to facilitate similarity search 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.
The initial release focuses strictly on the core functionality of the software. That is, to offer similarity search that work with large collections of samples. Technically, our approach is a combination of feature extraction, machine learning and modern web technologies.
The plan is to refine the software based on the feedback we receive, and to bring the Sononym experience to even more platforms.