| Publication Type |
Conference Paper |
| Authors |
Mirco Rossi, Gerhard Tröster, Oliver Amft |
| Title |
Recognizing Daily Life Context using Web-Collected Audio Data |
| Abstract |
This work presents an approach to model daily life contexts from web-collected audio data. Being available in vast quantities from many different sources, audio data from the web provides heterogeneous training data to construct recognition systems. Crowd-sourced textual descriptions (tags) related to individual sound samples were used in a configurable recognition system to model 23 sound context categories. We analysed our approach using different outlier filtering techniques with dedicated recordings of all 23 categories and in a study with 230 hours of full-day recordings of 10 participants using smart phones. Depending on the outlier technique, our system achieved recognition accuracies between 51% and 80%. |
| Date |
2012 |
| Proceedings Title |
Proceedings of the IEEE International Symposium on Wearable Computers (ISWC '12) |
| Publisher |
IEEE |
| Pages |
25–28 |
| DOI |
10.1109/ISWC.2012.12 |
| Full Text |
PDF |
