Jesse English and Sandor Dornbush With help from: Dr. Zary Segall & Chad Eby.

Slides:

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Presentation transcript:

Jesse English and Sandor Dornbush With help from: Dr. Zary Segall & Chad Eby.

Activity Awareness Feedback loop between the user and their music. Use the users physiological state to influence the music selection. The music influences the users mood and mindset.

Proposed XPod Form Factor

Proposed XPod User Interface

Potential XPod Platform Nokia 5500 Sport Phone Embedded Accelerometers MP3 Player

Experimental XPod Bodymedia Device Tablet

Music and Human Activity Music has a strong connection with human activity. People like to play music that is appropriate for their current activity. Music will can affect a persons mental state and physical activity.

Music Selection Choose the song that the user would most likely like in this state. Use the user prior behavior to learn their preferences. Combine a star rating system with body information.

Song Selection Choose a Song Randomly Learning Algorithm Estimate Preference Flip coin weighted by the Estimated preference Play Song Tails Heads

Results

XPod creates a custom context aware playlist. The addition of state information can improve the accuracy of the learning system. – Prefrence(Song|Time,Activity) ≠ Preference(Song) Neural Network seems to be best. – Generalizes best – Over trains very quickly SMO gets the exact. – Does not generalize well.

Network Structure 289 Input neurons 1 Output neuron 1-50 Hidden neurons – 4 is the best

Future Work Develop a prototype device. – Nokia 5500 Sport – iPaq and Backpaq Incorporate song metadata – Human Generated, eg Last.fm – Machine Generated Incorporate other meta information – Location Information – Recent Phone Calls – Weather

Questions?