HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset
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Abstract (arXiv)
Mosquitoes are the only known vector of malaria, which leads to hundreds of thousands of deaths each year. Understanding the number and location of potential mosquito vectors is of paramount importance to aid the reduction of malaria transmission cases. In recent years, deep learning has become widely used for bioacoustic classification tasks. In order to enable further research applications in this field, we release a new dataset of mosquito audio recordings. With over a thousand contributors, we obtained 195,434 labels of two second duration, of which approximately 10 percent signify mosquito events. We present an example use of the dataset, in which we train a convolutional neural network on log-Mel features, showcasing the information content of the labels. We hope this will become a vital resource for those researching all aspects of malaria, and add to the existing audio datasets for bioacoustic detection and signal processing.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 14 Jan 2020.
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- 2021HumBugDB: A Large-scale Acoustic Mosquito Datasetcited by 15
- 2021HumBugDB: A Large-scale Acoustic Mosquito Dataset14 Oct 2021