InsectSound1000 An insect sound dataset for deep learning based acoustic insect recognition.

Journal: Scientific data
PMID:

Abstract

InsectSound1000 is a dataset comprising more than 169000 labelled sound samples of 12 insects. The insect sound level spans from very loud (Bombus terrestris) to inaudible to human ears (Aphidoletes aphidimyza). The samples were extracted from more than 1000 h of recordings made in an anechoic box with a four-channel low-noise measurement microphone array. Each sample is a four-channel wave-file of 2500 kHz length, at 16 kHz sample rate and 32 bit resolution. Acoustic insect recognition holds great potential to form the basis of a digital insect sensor. Such sensors are desperately needed to automate pest monitoring and ecological monitoring. With its significant size and high-quality recordings, InsectSound1000 can be used to train data-hungry deep learning models. Used to pretrain models, it can also be leveraged to enable the development of acoustic insect recognition systems on different hardware or for different insects. Further, the methodology employed to create the dataset is presented in detail to allow for the extension of the published dataset.

Authors

  • Jelto Branding
    Julius Kühn Institute (JKI), Institute for Application Techniques in Plant Protection, Braunschweig, 38104, Germany. jelto.branding@julius-kuehn.de.
  • Dieter von Hörsten
    Julius Kühn Institute (JKI), Institute for Application Techniques in Plant Protection, Braunschweig, 38104, Germany.
  • Elias Böckmann
    Institute for Plant Protection in Horticulture and Forests, Julius Kühn-Institut, Messeweg 11-12, 38104, Braunschweig, Germany.
  • Jens Karl Wegener
    Julius Kühn Institute (JKI), Institute for Application Techniques in Plant Protection, Braunschweig, 38104, Germany.
  • Eberhard Hartung
    Department of Agricultural Engineering, Kiel University, Kiel, Germany.