| 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: - (Project) XPod has related publication (Publication) XPod: A Human Activity Aware Learning Mobile Music Player
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UMBC eBiquity Research Areas
