XPod: A Human Activity Aware Learning Mobile Music Player
The XPod system, presented in this paper, 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.
Date: January 08, 2007
Book Title: Proceedings of the Workshop on Ambient Intelligence, 20th International Joint Conference on Artificial Intelligence (IJCAI-2007)
Type: InProceedings
Edition: 2007
Downloads: 1248
Has 1 soft copy
size 170862 bytesBibtex
@InProceedings{XPod_A_Human_Activity_Aware_Learning_Mob,
author = "Sandor Dornbush and Jesse English and Tim Oates and Zary Segall and Anupam Joshi",
title = "{XPod: A Human Activity Aware Learning Mobile Music Player}",
month = "January",
year = "2007",
edition = "2007",
booktitle = "Proceedings of the Workshop on Ambient Intelligence, 20th International Joint Conference on Artificial Intelligence (IJCAI-2007)",
}