UMBC ebiquity

XPod

Status: Past project

Project Description:
The XPod system aims to integrate awareness of human activity and musical preferences to produce an adaptive system that plays the contextually correct music. The XPod project introduces a “smart” music player that learns its user’s preferences and activity, and tailors its music selections accordingly. We are using a BodyMedia device that has been shown to accurately measure a user’s physiological state. The device is able to monitor a number of variables to determine its user’s levels of activity, motion and physical state so that it may predict what music is appropriate at that point. The XPod user trains the player to understand what music is preferred and under what conditions. After training, the XPod, using various machine-learning techniques, is able to predict the desirability of a song, given the user’s physical state.

Start Date: January 2004

End Date: June 2008

Students:
Sandor Dornbush

Tags: music, mp3, learning, hci

 

There are 2 associated publications:
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Research Areas:
 Context-Aware Computing
 Mobile Computing
 Pervasive computing

 

Assertions:

  1. (Project) XPod has related publication (Publication) XPod: A Human Activity Aware Learning Mobile Music Player