Mood Adaptive Playlists
Whilst listening to my iPod on the train to work today, I had an idea, albeit probably not applicable to the iPod.
The basic story goes that, I’d say most people like to listen to different genres of music at different times. Unless you have a restricted musical taste, you probably like at least a few genres of music, and usually you like to listen to them on different occasions. I think the genre and mood of the music you like to listen to reflect what’s going on in your life and how you feel at that particular moment.
Due to the fact that we express how we feel through facial expressions and our actions, a computer could theoretically detect how you’re feeling. I know this isn’t the whole story, but nothings black and white.
So my idea is that, through using say a webcam (a Mac with an iSight would be ideal), we could combine facial recognition and emotion detection algorithms to form smart playlists that relates to your mood. This could even be combined with Genius in iTunes to form a set of songs that go well together and express your mood at the same time. I see the emotion detection algorithms being adaptive, relying on the image processing but also user input e.g. if the user chooses to skip a given song.
There are obviously some technical and privacy issues. The first technical issue being that image processing is very processor intensive, however with machines of the future having tens of cores, this may not be such a problem. Many users may also not want a computer detecting how they feel, or attempting to.
Now if only my iTunes COM interface worked properly I’d start coding it!