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| Content Provider | ACM Digital Library |
|---|---|
| Author | Reddy, Sasank Mascia, Jeff |
| Abstract | Advances in sensing technology and wider availability of network services is beckoning the use of context-awareness in ubiquitous computing applications. One region in which these technologies can play a major role is in the area of entertainment. Particularly, context-awareness can be used to provide higher quality interaction between humans and the media they are interacting with. We propose a music player, Lifetrak, that is in tune with a person's life by using a context-sensitive music engine to drive what music is played. This context engine is influenced by (i) the location of the user, (ii) the time of operation, (iii) the velocity of the user, and (iv) urban environment information such as traffic, weather, and sound modalities. Furthermore, we adjust the context engine by implementing a learning model that is based on user feedback on whether a certain song is appropriate for a particular context. Also, we introduce the idea of a context equalizer that adjusts how much a certain sensing modality affects what song is chosen. Since the music player will be implemented on a mobile device, there is a strong focus on creating a user interface that can be manipulated by users on the go. The goal of Lifetrak is to liberate a user from having to consciously specify the music that they want to play. Instead, Lifetrak intends to create a music experience for the user that is in rhythm with themselves and the space they reside in. |
| Starting Page | 25 |
| Ending Page | 34 |
| Page Count | 10 |
| File Format | |
| ISBN | 1595935002 |
| DOI | 10.1145/1178745.1178754 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2006-10-27 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Context Entertainment Music Sensors Mobile |
| Content Type | Text |
| Resource Type | Article |
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