Accession Number : ADA600404


Title :   Automated Acoustic Identification of Bats


Descriptive Note : Final rept. Aug 2004-Mar 2011


Corporate Author : HUMBOLDT STATE UNIV ARCATA CA


Personal Author(s) : Szewczak, Joseph M ; Parsons, Stuart ; Morrison, Michael L


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a600404.pdf


Report Date : Oct 2011


Pagination or Media Count : 87


Abstract : This project developed a monitoring system to automatically and continuously monitor bats and birds for weeks to months by recording the vocalizations they produce. This project combined more than 10,000 sequences of species-known bat echolocation call recordings from 37 species in 30 states. High-resolution, full-spectrum data enabled an intelligent routine to automatically track call trends through noise and echoes and to extract and quantify subtle signal parameters, and enable the assessment of signal properties for quality control. The compiled known data supported the creation of an expert system to classify similarly parameterized unknown data. The expert classification of calls, and sequences of calls, uses an ensemble consensus of redundant hierarchical decision algorithms that reports a single species decision only when a result meets or exceeds an acceptance threshold at each decision step and satisfies redundant checks and signal assessments. Because of the greater number of bird species, their complexity, and variety of calls and songs, this project adopted an alternate approach to recognize target signals for bird signal recognition.


Descriptors :   *ACOUSTIC DETECTION , *BATS , *BIRDS , *IDENTIFICATION , *TARGET RECOGNITION , ALGORITHMS , COMPUTER PROGRAMS , DISCRIMINANT ANALYSIS , ECHO RANGING , ENDANGERED SPECIES , FAST FOURIER TRANSFORMS , MONITORING , NEURAL NETS , PROBABILITY , RECOGNITION , RECORDING SYSTEMS


Subject Categories : Biology
      Acoustic Detection and Detectors
      Target Direction, Range and Position Finding


Distribution Statement : APPROVED FOR PUBLIC RELEASE