title: Automated bioacoustic identification of species.
abstract: Research into the automated identification of animals by bioacoustics is becoming more widespread mainly due to difficulties in carrying out manual surveys. This paper describes automated recognition of insects (Orthoptera) using time domain signal coding and artificial neural networks. Results of field recordings made in the UK in 2002 are presented which show that it is possible to accurately recognize 4 British Orthoptera species in natural conditions under high levels of interference. Work is under way to increase the number of species recognized.
authors.affiliation: Intelligent Systems Research Group, Department of Electronics, University of York, Heslington, York, England. edc1@ohm.york.ac.uk
authors.forename: David
authors.initials: D
authors.lastname: Chesmore
mesh_terms: D000162:Acoustics / Q000295:instrumentation*; D000818:Animals; D001330:Electronic Data Processing / Q000379:methods*; D016571:Neural Networks, Computer; D009987:Orthoptera / Q000145:classification* / Q000502:physiology; D006113:United Kingdom; D014828:Vocalization, Animal