Abstract
This dataset can be found on Zenodo: https://doi.org/10.5281/zenodo.6478589
A large-scale multi-species dataset of acoustic recordings
Dataset compatible with two papers:
The Computational Paralinguistics ChallengE (ComParE): Mosquito Event Detection Task https://github.com/EIHW/ComParE2022/tree/MOS-C
An update to: HumBugDB: a large-scale acoustic mosquito dataset: NeurIPS 2021 Paper
https://github.com/HumBug-Mosquito/HumBugDB.
A large-scale multi-species dataset containing recordings of mosquitoes collected from multiple locations globally, as well as via different collection methods. In total, we present 20 hours of labelled mosquito data with 15 hours of corresponding background noise, recorded at the sites of 8 experiments. Of these, 64,843 seconds contain species metadata, consisting of 36 species (or species complexes).
This repository contains:
Audio files to be extracted into audio/data/train and audio/data/dev/{a/b} respectively
Metadata in csv format: neurips_2021_zenodo_0_0_2.csv
Funding from the 2014 Google Impact Challenge Award, and The Bill and Melinda Gates Foundation (https://www.gatesfoundation.org/about/committed-grants/2019/07/opp1209888)