Title :
Decision templates for the classification of bioacoustic time series
Author :
Dietrich, Christian ; Schwenker, Friedhelm ; Palm, Günther
Author_Institution :
Dept. of Neural Inf. Process., Ulm Univ., Germany
Abstract :
The classification of time series is topic of this paper. In particular we discuss the combination of multiple classifier outputs with decision templates. The decision templates are calculated over a set of feature vectors which are extracted in local time windows. To learn characteristic classifier outputs of time series a set of decision templates is determined for the individual classes. We present algorithms to calculate multiple decision templates, and demonstrate the behaviour of this new approach on a real world data set from the field of bioacoustics.
Keywords :
bioacoustics; decision theory; feature extraction; neural nets; time series; bioacoustic time series; classification; feature vector extraction; local time windows; multiple classifier outputs; multiple decision templates; neural networks; Biomedical acoustics; Data mining; Hidden Markov models; Information processing; Neural networks; Recurrent neural networks; Signal processing; Speech processing; Speech recognition; Supervised learning;
Conference_Titel :
Neural Networks for Signal Processing, 2002. Proceedings of the 2002 12th IEEE Workshop on
Print_ISBN :
0-7803-7616-1
DOI :
10.1109/NNSP.2002.1030027
