Searching for new music can be a daunting task. Services like Apple’s iTunes or the website last.fm make it relatively easy to find music similar to songs or artists you already listen to. But type in “instrumentals for yoga class” and you probably won’t get very far.
Luke Barrington, a PhD student at the University of California San Diego, plans to change that with the beta version of his music search engine, Herd It, which he launched last week. His goal is to find and recommend music based on natural-language searches, providing users with both familiar and new songs that share acoustic qualities.
When he recently pitted his recommendation software against Apple’s music recommendation system, Genius, he found that users were equally satisfied with playlists suggested by both methods.