Black-and-white ruffed lemur (Varecia variegata) calls for passive acoustic monitoring
Creators
- 1. Graduate Center of the City University of New York, New York City, NY, USA
- 2. Centre ValBio, Ranomafana, Madagascar
- 3. University of Antananarivo, Antananarivo, Madagascar
- 4. Graduate Center of the City University of New York, New York City, NY, USA; Hunter College, City University of New York, New York City, NY, USA
- 5. Stellenbosch University; African Institute for Mathematical Sciences
Description
Data accompanying the paper: "Passive Acoustic Monitoring and Transfer Learning"
Please cite this dataset as:
Dufourq, Emmanuel and Batist, Carly and Foquet, Ruben and Durbach, Ian. (2022). Passive Acoustic Monitoring and Transfer Learning. BioRxiv doi:
This dataset contains approximately 60 hours of audio that contained calls of the critically endangered Black-and-white ruffed lemur (Varecia variegata). The audio data was collected in a sub-humid rainforest site (Mangevo) in the southeast of Ranomafana National Park in Madagascar using 2 Swift recorders (Cornell Center for Conservation Bioacoustics). The sampling rate was set to 48,000Hz and the recordings were collected intermittently between May 2019 and November 2020. A larger dataset exists and further recordings will be released.
The annotations files are in (.svl) format which is compatible with SonicVisualiser (https://www.sonicvisualiser.org/). Each audio file has a corresponding .svl file. Each .svl has segments of audio that were manually annotated as either ''thyolo-alethe" (presence class) or "noise" (absence class) -- this dataset can be used to train a binary classification model.
The audio files are provided in "Audio.zip" and the manually verified annotation in "Annotations.zip".
Notes
Files
Annotations1.zip
Files
(13.3 GB)
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