| Autor: |
Jelto Branding, Dieter von Hörsten, Elias Böckmann, Jens Karl Wegener, Eberhard Hartung |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Scientific Data, Vol 11, Iss 1, Pp 1-18 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2052-4463 |
| DOI: |
10.1038/s41597-024-03301-4 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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