New Search by Sound feature live on Airbit, built to surface beats that sound right, not tags
Airbit, the beat marketplace committed to supporting sustainable careers for producers, is launching Search by Sound, a simple, ingenious way artists can find their next awesome beat. Search by Sound lets beat seekers pop a file or link into the search bar. The first of its kind in the space, the Search by Sound technology removes vocals, which can skew results, and finds just the right sounding beat, often by emerging producers making hidden gems.
These gems have too often laid buried, overlooked by algorithms and tag-based search. Airbit’s Search by Sound uses machine learning-based audio analysis to find sonic similarity between tracks, regardless of producer hype, tags, or other factors. This changes the game for beat discovery.
The curious can try it for themselves here.
In the world of buying and selling beats, producers have traditionally angled to be discovered by beat seekers via type beats, tags or file names that bake the name of a star artist into the beat’s name, making it easier (in theory) for recording artists to find something in a style they already know and love.
“Type beats aren’t bad in and of themselves; in fact, type beats have been one of the only tools producers and artists have had to find each other,” explains Wasim Khamlichi, Airbit founder and CEO. “Type beats are the symptom, not the disease. They get in the way of truly talented people getting their work out there, and of music fans finding truly good and creative music. It's a dilemma for both new talent and curious fans.”
When type beats first emerged on YouTube thanks to producers like Cashmoneyap, they connected producers and beat seekers. Talented young producers were struggling to be heard, and type beats were one weapon in that struggle. When artists or MCs were searching for beats to use, with YouTube as the search engine of choice, they would have to describe the sound of the beat they wanted, and the easiest way to do this was naming an artist. Then things got messy: The self-reported nature of type beats meant they were often inaccurate. “There is a perverse incentive to mislead, because people want to be discovered,” Khamlichi notes. “That makes this approach a frustrating experience for the end user.”
Airbit wanted to improve the experience for both parties, by removing human bias and ensuring producers get in front of prospective beats buyers on the merit of their beats, not their tagging hustle. It’s part of a bigger mission to support producers, veteran and new, as they create more sustainable careers and businesses. “We want good producers with great beats to get discovered, so that artists can make the amazing tracks they hear in their heads,” says Khamlichi. “AI and better search were the way to make that happen and build a more meritocratic marketplace.”