Xeno-canto

xeno-canto is a citizen science project and repository in which volunteers record, upload and annotate recordings of birdsong and bird calls. Since it began in 2005, it has collected over 400,000 sound recordings from more than 10,000 species worldwide, and has become one of the biggest collections of bird sounds in the world.[2] All the recordings are published under one of the Creative Commons licenses,[3] including some with open licences.

xeno-canto
Type of site
Audio clip sharing
Available in
  • English
  • Dutch
  • Polish
URLwww.xeno-canto.org
Alexa rank 281,023 (July 2020)[1]
CommercialNo
RegistrationOptional
LaunchedMay 30, 2005 (2005-05-30)[2]
Current statusActive

Data from xeno-canto has been re-used in many scientific papers.[4][5][6][7] It has also been the source of data for an annual challenge on automatic birdsong recognition ("BirdCLEF") since 2014, conducted as part of the Conference and Labs of the Evaluation Forum.[8]

The website is supported by a number of academic and birdwatching institutions worldwide, with its primary support being in the Netherlands.[9]

References
  1. "xeno-canto.org Competitive Analysis, Marketing Mix and Traffic - Alexa". alexa.com. Retrieved 2020-07-21.
  2. "About Xeno Canto". xeno-canto. Retrieved 2019-04-16.
  3. "Terms of Use". xeno-canto. Retrieved 2013-01-07.
  4. Brumm, H. & Naguib, M. (2009), "Environmental acoustics and the evolution of bird song", Advances in the Study of Behavior, 40: 1–33, doi:10.1016/S0065-3454(09)40001-9
  5. Weir, J.T. & Wheatcroft, D. (2011), "A latitudinal gradient in rates of evolution of avian syllable diversity and song length", Proceedings of the Royal Society B: Biological Sciences, 278 (1712): 1713–1720, doi:10.1098/rspb.2010.2037, PMC 3081773, PMID 21068034
  6. Stowell, D.F. & Plumbley, M. D. (2014), "Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning", PeerJ, 2: e488, arXiv:1405.6524, Bibcode:2014arXiv1405.6524S, doi:10.7717/peerj.488, PMC 4106198, PMID 25083350
  7. Stowell, D.F.; Musevic,S.; Bonada,J. & Plumbley, M. D. (2013), "Improved multiple birdsong tracking with distribution derivative method and Markov renewal process clustering", 2013 IEEE International Conference on Acoustics, Speech and Signal Processing: 468–472, arXiv:1302.3462, Bibcode:2013arXiv1302.3462S, doi:10.1109/ICASSP.2013.6637691, hdl:10230/41749, ISBN 978-1-4799-0356-6
  8. BirdCLEF 2019 webpage
  9. "Colophon and Credits". xeno-canto. Retrieved 2013-01-07.


This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.