Using image processing to detect and classify narrow-band cricket and frog calls

Journal of the Acoustical Society of America

Volumn 120, Issue 5, 2006, Pages 2950-2957

  Brandes, T Scott ^a   Naskrecki, Piotr ^b   Figueroa, Harold K ^c  

^a Tropical Ecology Assessment and Monitoring   (United States)

^b HARVARD UNIVERSITY   (United States)

^c Fuller Evolutionary Biology Program   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BANDWIDTH; CLASSIFICATION (OF INFORMATION); IDENTIFICATION (CONTROL SYSTEMS); SPECTROGRAPHS;

AUTOMATIC CALL RECOGNITION (ACR); BAYESIAN CLASSIFIERS; SONOTYPES; THRESHOLDING FILTERS;

IMAGE PROCESSING;

ACOUSTICS; ANIMAL EXPERIMENT; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; COSTA RICA; FILTER; FREQUENCY MODULATION; FROG; IMAGE PROCESSING; NONHUMAN; PRIORITY JOURNAL; RAIN FOREST; SOUND DETECTION; SOUND INTENSITY;

ACOUSTIC STIMULATION; ALGORITHMS; ANIMALS; ANURA; COSTA RICA; GRYLLIDAE; IMAGE PROCESSING, COMPUTER-ASSISTED; SOUND SPECTROGRAPHY; TREES; VOCALIZATION, ANIMAL;

EID: 33750315192     PISSN: 00014966     EISSN: None     Source Type: Journal    
DOI: 10.1121/1.2355479     Document Type: Article

References (26)

1. P. F. Fischer, U. Schulz, H. Schubert, P. Knapp, and M. Schmöger, " Quantitative assessment of grassland quality: Acoustic determination of population sizes of Orthopteran indicators species., " Ecol. Appl. 7, 909-920 (1997).
2. W. J. Bailey, Acoustic Behaviour of Insects. An Evolutionary Perspective (Chapman and Hall, London, 1991).
3. K. Riede, " Acoustic monitoring of Orthoptera and its potential for conservation., " Journal of Insect Conservation 2, 217-223 (1998).
4. T. J. Walker, " Cryptic species among sound-producing ensiferan Orthoptera (Gryllidae and Tettigoniidae)., " Q. Rev. Biol. 39, 345-355 (1964).
5. D. Otte, " The crickets of Hawaii: Origin, systematics and evolution., " Orthopterists' Society, Philadelphia, pp. 1-396 (1994).
6. D. R. Ragge and W. J. Reynolds, The Songs of the Grasshoppers and Crickets of Western Europe (Harley, Colchester, 1998).
7. L. Desutter-Grandcolas (personal communication).
8. D. Otte (personal communication).
9. C. Froehlich and E. Holtzem, " Eine neue Methode zum Auffinden und Bestimmen von Heuschrecken (Saltatoria) im Freiland., " Z. angew. Zool. 74, 501-503 (1987).
10. F. Nischk and K. Riede, " Bioacoustics of two cloud forest ecosystems in Ecuador compared to lowland rainforest with special emphasis on singing cricket species., " in Epiphytes and Canopy Fauna of the Otongan Rain Forest (Ecuador). Results of the Bonn-Quito Epiphyte Project, Funded by the Volkswagen Foundation, edited by, J. Nieder, and, W. Barthlott, (2001), Vol. 2, pp. 217-242.
11. N. Vaughan, G. Jones, and S. Harris, " Identification of British bat species by multivariate analysis of echolocation call parameters., " Bioacoustics 7, 189-207 (1997).
12. S. Parsons and G. Jones, " Acoustic identification of 12 species of echolocating bats by discriminant function analysis and artificial neural networks., " J. Exp. Biol. 203, 2641-2656 (2000).
13. S. Parsons, " Identification of New Zealand bats in flight from analysis of echolocation call by artificial neural networks., " J. Zool. 253, 447-456 (2001).
14. S. E. Anderson, A. S. Dave, and D. Margoliash, " Template-based automatic recognition of birdsong syllables from continuous recordings., " J. Acoust. Soc. Am. 100, 1209-1219 (1996).
15. J. A. Kogan and D. Margoliash, " Automated recognition of bird song elements from continuous recordings using dynamic time warping and hidden Markov models: A comparative study., " J. Acoust. Soc. Am. 103, 2185-2196 (1998).
16. A. Taylor, G. Watson, G. Grigg, and H. McCallum, " Monitoring frog communities: An application of machine learning., " in Proceedings of the 8th Innovative Applications of Artificial Intelligence Conference (1996), pp. 1564-1596.
17. E. D. Chesmore, O. P. Femminella, and M. D. Swarbrick, " Automated analysis of insect sounds using time-encoded signals and expert systems-A new method for species identification., " in Information Technology, Plant Pathology and Biodiversity, edited by, P. Bridge,,, P. Jeffries,,, D. R. Morse,, and, P. R. Scott, (CAB International, Wallinford, 1998), pp. 273-287.
18. E. D. Chesmore, " Application of time domain signal coding and artificial neural networks to passive acoustical identification of animals., " Appl. Acoust. 62, 1359-1374 (2001).
19. C. Dietrich, G. Palm, K. Riede, and F. Schwenker, " Classification of bioacoustic time series based on the combination of global and local decisions., " Int. J. Pattern Recognit. Artif. Intell. 37, 2293-2305 (2004).
20. C. Xu, N. C. Maddage, and X. Shao, " Automatic music classification and summarization., " IEEE Trans. Speech Audio Process. 13, 441-450 (2005).
21. L. R. Rabiner and B. H. Juang, Fundamentals of Speech Recognition (Prentice-Hall, New Jersey, 1993).
22. K. Riede, " Bioacoustic monitoring of insect communities in a Bornean rain forest canopy., " in Canopy Arthropods, edited by, N. E. Stork,,, J. Adis,, and, R. K. Didham, (Chapman and Hall, London, 1997), pp. 442-452.
23. T. S. Brandes, " Acoustic Monitoring Protocol., " Tropical Ecology Assessment and Monitoring (TEAM) Initiative set of biodiversity monitoring protocols, Center for Applied Biodiversity Science, Conservation International (2005), http://www.teaminitiative.org (navigate to "Protocols") (last visited September 2006).
24. T. J. Walker, " Factors responsible for intraspecific variation in the calling songs of crickets., " Evolution (Lawrence, Kans.) 16, 407-428 (1962).
25. H. C. Gerhardt and F. Huber, Acoustic Communication in Insects and Anurans, Common Problems and Diverse Solutions (University of Chicago Press, Chicago, 2002).
26. E. Diday, " The dynamic clusters method in nonhierarchical clustering., " Int. J. Comput. Inf. Sci. 2, 61-68 (1973).