Cane Toad Acoustic Classifier Audio Training Data

Cane Toad Audio Dataset for Machine Learning Classifier Development

Description:

This dataset was created as part of a study aimed at developing a machine learning classifier to detect the advertisement calls of the cane toad (Rhinella marina) using BirdNET. The dataset comprises 3-second audio snippets that capture a variety of sounds, including cane toad vocalizations, calls from spectrally overlapping species, environmental noises, and unidentified sounds. These labelled sound data were collected from various Australian Acoustic Observatory' recording sites, covering a broad range of geographic locations and environmental conditions in Australia.

Sound Classes:

• Background
• Canis lupus dingo (Dingo)
• Centropus phasianinus (Pheasant Coucal)
• Cyclorana australis (Water Holding Frog)
• Cyclorana cryptotis (Hidden Ear Frog)
• Cyclorana novaehollandiae (New Holland Frog)
• Dacelo novaeguineae (Kookaburra)
• Ninox boobook (Southern Boobook)
• Notaden melanoscaphus (Northern Spadefoot Toad)
• Rhinella marina (Cane Toad) – Processed with a low-pass filter to remove frequencies above 1300 Hz, minimizing interference from co-occurring sounds.
• Unidentified Sounds

Use and Applications:

This dataset is valuable for training machine learning models focused on the acoustic detection of cane toads, could be useful for researchers and professionals working in bioacoustics, machine learning, ecological monitoring and invasive species management.