|
|
|
|
| LEADER |
01273 am a22002293u 4500 |
| 001 |
60225 |
| 042 |
|
|
|a dc
|
| 100 |
1 |
0 |
|a Van Kleek, Max G.
|e author
|
| 100 |
1 |
0 |
|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
|e contributor
|
| 100 |
1 |
0 |
|a van Kleet, Max G.
|e contributor
|
| 100 |
1 |
0 |
|a Van Kleek, Max G.
|e contributor
|
| 700 |
1 |
0 |
|a Perttunen, Mikko
|e author
|
| 700 |
1 |
0 |
|a Lassila, Ora
|e author
|
| 700 |
1 |
0 |
|a Riekki, Jukka
|e author
|
| 245 |
0 |
0 |
|a An implementation of auditory context recognition for mobile devices
|
| 260 |
|
|
|b Institute of Electrical and Electronics Engineers,
|c 2010-12-08T16:22:15Z.
|
| 856 |
|
|
|z Get fulltext
|u http://hdl.handle.net/1721.1/60225
|
| 520 |
|
|
|a Auditory contexts are recognized from mixtures of sounds from mobile userspsila everyday environments. We describe our implementation of auditory context recognition for mobile devices. In our system we use a set of support vector machine classifiers to implement the recognizer. Moreover, static and runtime resource consumption of the system are measured and reported.
|
| 520 |
|
|
|a Nokia Research Center
|
| 546 |
|
|
|a en_US
|
| 655 |
7 |
|
|a Article
|
| 773 |
|
|
|t Tenth International Conference on Mobile Data Management: Systems, Services and Middleware, 2009. MDM '09
|
