Mooso
We've just launched the latest Radio Labs prototype: . It's a game you play while listening to 6 Music, in which you enter tags and suggest similar artists to describe the current track. If what you enter matches what other players enter you get points. We give more points for matching similar artists than tags and you also get a point just for playing.
How to play... in three easy steps
Step 1: Listen to 6 Music.
On your digital radio, TV or on the web it doesn't matter. 6 Music will automatically start playing when you hit Play on the site.
Step 2: Enter tags and similar artists for the track playing.
Hit the Play button on the site to open the pop-up play window. When a song plays on 6 Music, a new round starts and you can start entering tags. Tags are words or short descriptions of the music that could be genres, instruments or even moods. You can also suggest similar artists (you get more points for this!) or anything else, it's up to you. But be quick, you've only got two minutes from the start of the song.
Step 3: Match tags and artists with other players to score points.
You get points by matching tags and similar artists with other players, but you can't see what those other players are entering so you'd better make sure you're entering good tags. For example in , the track played was 'New Fang' by Them Crooked Vultures and the players matched with the tags and and with artists , , , and . The more tags you match with other players the more points you win, the higher up the leaderboard you go and the closer you are to becoming a Mooso.
You can play between 7am and 7pm Monday to Friday along to Shaun Keaveny, Lauren Laverne, Cerys and Steve Lamacq. The more people playing the better, so why not join in at lunch time with Cerys' slot at 1?
Sign up and join in
There are a couple of ways in which you can join in and start playing. You can sign up on the web site (OpenID is supported) and play in your web browser (you'll need Flash Player 9+ and either Chrome, Firefox 3+, Internet Explorer 7+, Opera 9+ or Safari 3+) or if you have a or account you can play over instant messenger. Simply add moose@mooso.fm to your contacts to start playing. More information is available at . You can also follow .
Game with a purpose
So what's the point? is a (or GWAP) - a game which while (hopefully) being fun to play, produces another useful output. Another GWAP is which collates user input to annotate images and make them easier to search for. With Mooso, we hope to generate some rich data which describes tracks and artists and links them all together which in turn can be used to help you discover new music. You can look back through on the Mooso site to see what people entered and browse through artists and tags which, we hope over time, will form an interesting web of information.
For example, navigating to displays the their suggested related artists and tags created in the game, along with a link to read more about them on 91Èȱ¬ Music.
You could say this is an investigation into user-generated music recommendation but we have designed Mooso first and foremost to be an entertaining game to play so please sign up, play, score points and tell us what you think.
was developed by Radio Labs in collaboration with 91Èȱ¬ R&D and 6 Music. We will also be posting about how it works and how we developed it.
Comment number 1.
At 5th Dec 2009, Richard Wright wrote:You mention a Google GWAP that works on pictures, but you don't mention tagging tools for time-based media -- such as audio. Perhaps you're only interested in the overall "object" -- in this case one 6Music 'song', but time-based media is richer than a picture. It is not only possible, but also useful and indeed interesting, to annotate specific time points. Software that supports time-based annotation of video, which has incidentally been demonstrated within the 91Èȱ¬, includes:
1) Yahoo Video Tag Game:
(which they appear to have patented:
www.faqs.org/patents/app/20090132935)
2) WAISDA:
Regards, Richard
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Comment number 2.
At 7th Dec 2009, tristanf wrote:Thanks for those links Richard. In this case we are primarily focussing in the song but more finely-tuned timed annotations are another possibility. It would certainly be interesting and challenging to think about how something like Mooso could work for speech radio.
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