The Helios Music Recommendation Engine is a powerful B2B technology to allow searching of large commercial music libraries by using music itself as the search key. Here are a few of the many possible uses for Helios:
Nearly always clients approach you with samples already in hand, possibly from your own catalogue. “Hey, do you have anything else like this?” This could be an MP3 or a YouTube video URL. Use the customer’s samples directly with Helios to help them find what they’re looking for.
Traditionally, in the absence of such technology, the way this has been done for decades may surprise many. It is both costly and involves many hours or even days of manual human labour which delays the business process. The business must manually search, usually using textual tags, and listen to a great deal of irrelevant music in the hopes of finding the one the client is actually willing to spend money on.
How does it work?
Helios works by analyzing the actual sound of each audio track it’s provided. This is called sub-symbolic analysis. It does this by performing a complex digital signal processing analysis on both time and spectral domains. It actually listens to your music rather than just guessing what you want based on what it thinks someone like you listened to before. The scientific research Helios was based on is extensive and draws upon topics in physics, mathematics, and computing science.