Home Mufin: Better Music Recommendations through Algorithms?

Mufin: Better Music Recommendations through Algorithms?

Music discovery is clearly a hot topic these days, with large companies like Apple and Microsoft competing with smaller services like imeem, Pandora, and Last.fm. With the exception of Pandora, these services typically rely on the listening habits and recommendations of other users.

Mufin.com, however, which launched today, uses a fully automated system that only takes the actual sounds of a song into consideration. In our tests, Mufin often returned good results, but the fact that it doesn’t take genres or the quality of a song into account can make for a frustrating experience at times.

Mufin’s interface is straightforward and stays out of the user’s way. Songs are played through a standard flash player and the AJAX-driven interface is fast and well designed, though it would be nice if you could play similar songs without having to click through to another page.

Eclectic Recommendations

There is something to be said for this completely algorithmic approach. While social recommendation services tend to return results that safely stay within the same genre as the original song, Mufin’s choices are far more eclectic. The most closely related song to Rick Astley’s seminal “Never Gonna Give You Up,” for example, is a song in Bavarian by a German folk pop group. Mufin really seems to like German songs, by the way, as more than half of the songs it recommended as similar to Frank Zappa’s “Muffin Man” were from a Sesame Street album in German. In Mufin’s defense, though, all these songs were quite similar in style to the original song.

Social Recommendations vs. Algorithms

As MG Siegler points out, the real advantage of social recommendation engines is that they are very good at filtering out bad music (though one might also argue that this can lead to slightly boring recommendations at times). Mufin neither cares about the quality of the music nor its popularity or language; it only looks at characteristics like tempo, instruments, sound density, and harmony.


Mufin has already built an extensive library of songs, but it only holds the right to a limited set of them, which means that you simply can’t play a lot of the recommended songs. Those songs that can be played are limited to 30-second previews , which can make it hard to decide if a song is really good and similar enough to warrant buying it.

If Mufin had partnered with a service like Rhapsody, for example, users would at least have been able to stream a limited number of full songs every month. Every song on Mufin features a link to iTunes and the Amazon music store.

Overall, we think Mufin is an interesting experiment, but we are not convinced that its algorithms return better recommendations than the more social approach of its competitors or the classification system of the Music Genome Project that drives Pandora’s recommendation engine.

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