Name
Title | ||
|---|---|---|
Acoustic detection and classification of sound sources using temporal multiple energy detector features |
Abstract | ||
|---|---|---|
In this work, a classification method using a novel approach for acoustic feature extraction is proposed. Therefore, a multiple energy detector structure (MED) is utilized and features called temporal MED (TMED) features are introduced. The usage of an energy detector enables a pre-classification for the differentiation between impulsive and non-impulsive acoustic events. The actual classification task can be performed by using a MED. Furthermore, investigations regarding the classification accuracy using more than one microphone are presented. |
Year | Venue | Field |
|---|---|---|
2009 | European Signal Processing Conference | Computer science,Speech recognition,Feature extraction,Detector,Microphone |
DocType | ISBN | Citations |
Conference | 978-161-7388-76-7 | 1 |
PageRank | References | Authors |
0.49 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexej Swerdlow | 1 | 7 | 1.84 |
| Timo Machmer | 2 | 7 | 1.84 |
| Kristian Kroschel | 3 | 510 | 47.69 |
| Jorge Moragues | 4 | 38 | 4.75 |
| Arturo Serrano | 5 | 46 | 7.04 |
| L. Vergara | 6 | 68 | 18.45 |