Birdsong Denoising Using Wavelets

PloS One
Nirosha PriyadarshaniAmal Punchihewa

Abstract

Automatic recording of birdsong is becoming the preferred way to monitor and quantify bird populations worldwide. Programmable recorders allow recordings to be obtained at all times of day and year for extended periods of time. Consequently, there is a critical need for robust automated birdsong recognition. One prominent obstacle to achieving this is low signal to noise ratio in unattended recordings. Field recordings are often very noisy: birdsong is only one component in a recording, which also includes noise from the environment (such as wind and rain), other animals (including insects), and human-related activities, as well as noise from the recorder itself. We describe a method of denoising using a combination of the wavelet packet decomposition and band-pass or low-pass filtering, and present experiments that demonstrate an order of magnitude improvement in noise reduction over natural noisy bird recordings.

References

May 16, 1970·Nature·D H Morse
Jul 7, 2007·The Journal of the Acoustical Society of America·Berke M Gur, Christopher Niezrecki
Jul 24, 2008·The Journal of the Acoustical Society of America·Yao RenJidong Tao
Dec 16, 2011·Computers in Biology and Medicine·Sergey VaismanAmir B Geva
May 24, 2014·Journal of Insect Physiology·A Arenas, W M Farina
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Citations

Oct 9, 2019·The Journal of the Acoustical Society of America·Fernando MerchanHector M Guzman
Jul 30, 2020·Ecology and Evolution·Tessa A RhinehartJustin Kitzes
Jun 8, 2018·Ecology and Evolution·Nirosha PriyadarshaniStephen Marsland
Jan 3, 2020·The Journal of the Acoustical Society of America·Benjamin OllivierYusuke Hioka

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Methods Mentioned

BETA
feature extraction

Software Mentioned

Wavelet Toolbox
STFT
Matlab

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