Datasetpublic

monster-monash/InsectSound

Part of MONSTER: https://arxiv.org/abs/2502.15122. InsectSound Category Audio Num. Examples 50,000 Num. Channels 1 Length 600 Sampling Freq. 6 kHz Num. Classes 10 License Public Domain Citations [1] [2] FruitFlies, taken from the broader UCR archive, consistst of 34,518 (univariate) time series, each of length 5,000, representing acoustic recordings of wingbeats for three species of fruit fly [1, 2]. The recordings are single channel with a sampling rate of 8 kHz… See the full description on the dataset page: https://huggingface.co/datasets/monster-monash/InsectSound.

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Dataset Card

Part of MONSTER: <https://arxiv.org/abs/2502.15122>.

InsectSound
Category	Audio
Num. Examples	50,000
Num. Channels	1
Length	600
Sampling Freq.	6 kHz
Num. Classes	10
License	Public Domain
Citations	[1] [2]

*FruitFlies*, taken from the broader UCR archive, consistst of 34,518 (univariate) time series, each of length 5,000, representing acoustic recordings of wingbeats for three species of fruit fly [1, 2]. The recordings are single channel with a sampling rate of 8 kHz (i.e., each recording represents just over half a second of data). The recordings are made using a specialised infrared sensor which detects the vibrations of the wings of the insects. The learning task is to identify the species of fly based on the recordings. This version of the dataset has been split into stratified random cross-validation folds.

[1] Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, and Eamonn Keogh. (2014). Flying insect classification with inexpensive sensors. Journal of Insect Behavior, 27(5):657–677.

[2] Yanping Chen. Flying insect classification with inexpensive sensors. https://sites.google.com/site/insectclassification/ (via Internet Archive), 2014. Public Domain.