C4.5: programs for machine learning
C4.5: programs for machine learning
Discrete Time Processing of Speech Signals
Discrete Time Processing of Speech Signals
IEEE Expert: Intelligent Systems and Their Applications
The design and evaluation of a hybrid sensor network for Cane-Toad monitoring
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Design and evaluation of a hybrid sensor network for cane toad monitoring
ACM Transactions on Sensor Networks (TOSN)
Automatic recognition of frog calls using a multi-stage average spectrum
Computers & Mathematics with Applications
Classification of underwater broadband bio-acoustics using spectro-temporal features
Proceedings of the Seventh ACM International Conference on Underwater Networks and Systems
Analysing environmental acoustic data through collaboration and automation
Future Generation Computer Systems
Real-time classification via sparse representation in acoustic sensor networks
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
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Automatic recognition of animal vocalisations would be a valuable tool for a variety of biological research and environmental monitoring applications. We report the development of a software system which can recognise the vocalisations of 22 species of frogs which occur in an area of northern Australia. This software system will be used in unattended operation to monitor the effect on frog populations of the introduced Cane Toad. The system is based around classification of local peaks in the spectrogram of the audio signal using Quinlan's machine learning system, C4.5 (Quinlan 1993). Unreliable identifications of peaks are aggregated together using a hierarchical structure of segments based on the typical temporal vocalisation species' patterns. This produces robust system performance.