BirdVox-70k: a dataset for species-agnostic flight call detection in half-second clips

BirdVox-70k: a dataset for avian flight call detection in half-second clips
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Version 1.0, April 2018.

Created By
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Vincent Lostanlen (1, 2, 3), Justin Salamon (2, 3), Andrew Farnsworth (1), Steve Kelling (1), and Juan Pablo Bello (2, 3).

(1): Cornell Lab of Ornithology (CLO)
(2): Center for Urban Science and Progress, New York University
(3): Music and Audio Research Lab, New York University

https://wp.nyu.edu/birdvox

Description
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The BirdVox-70k dataset contains 70k half-second clips from 6 audio recordings in the BirdVox-full-night dataset, each about ten hours in duration. These recordings come from ROBIN autonomous recording units, placed near Ithaca, NY, USA during the fall 2015. They were captured on the night of September 23rd, 2015, by six different sensors, originally numbered 1, 2, 3, 5, 7, and 10.

Andrew Farnsworth used the Raven software to pinpoint every avian flight call in time and frequency. He found 35402 flight calls in total. He estimates that about 25 different species of passerines (thrushes, warblers, and sparrows) are present in this recording. Species are not labeled in BirdVox-70k, but it is possible to tell apart thrushes from warblers and sparrrows by looking at the center frequencies of their calls. The annotation process took 102 hours.

The dataset can be used, among other things, for the research,development and testing of bioacoustic classification mode ls, including the reproduction of the results reported in [1].

For details on the hardware of ROBIN recording units, we refer the reader to [2].

[1] V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection. Proc. IEEE ICASSP, 2018.

[2] J. Salamon, J. P. Bello, A. Farnsworth, M. Robbins, S. Keen, H. Klinck, and S. Kelling. Towards the Automatic Classification of Avian Flight Calls for Bioacoustic Monitoring. PLoS One, 2016.

@inproceedings{lostanlen2018icassp,
  title = {BirdVox-full-night: a dataset and benchmark for avian flight call detection},
  author = {Lostanlen, Vincent and Salamon, Justin and Farnsworth, Andrew and Kelling, Steve and Bello, Juan Pablo},
  booktitle = {Proc. IEEE ICASSP},
  year = {2018},
  published = {IEEE},
  venue = {Calgary, Canada},
  month = {April},
}

Data Files
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BirdVox-70k contains the recordings as HDF5 files, sampled at 24 kHz, with a single channel (mono). Each HDF5 file corresponds to a different sensor. The name of the HDF5 dataset in each file is "waveforms".

Metadata Files
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Contrary to BirdVox-full-night, BirdVox-70k is not shipped with a metadata file. Rather, the metadata is included in the keys of the elements in the HDF5 files themselves, whose values are the waveforms.

An example of BirdVox-70k key is:

unitID_TIMESTAMP_FREQ_LABEL

where

• ID is the identifier of the unit (01, 02, 03, 05, 07, or 10)
• TIMESTAMP is the timestamp of the center of the clip in the BirdVox-full-night recording. This timestamp is measured in samples at 24 kHz. It is accurate at about 10 ms.
• FREQ is the center frequency of the flight call, measured in Hertz. It is accurate at about 1 kHz. When the clip is negative, i.e. does not contain any flight call, it is set equal to zero by convention.
• LABEL is the label of the clip, positive (1) or negative (0).

Example:

unit01_085256784_03636_1

is a positive clip in unit 01, with timestamp 085256784 (3552.37 seconds after dividing by the sample rate 24000), center frequency 3636 Hz.

Another example:

unit05_284775340_00000_0

is a negative clip in unit 05, with timestamp 284775340 (11865.64 seconds).

The approximate GPS coordinates of the sensors (latitudes and longitudes rounded to 2 decimal points) and UTC timestamps corresponding to the start of the recording for each sensor are included as CSV files in the main directory.

Please acknowledge BirdVox-70k in academic research
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When BirdVox-70k is used for academic research, we would highly appreciate it if  scientific publications of works partly based on this dataset cite the following publication:

V. Lostanlen, J. Salamon, A. Farnsworth, S. Kelling, J. Bello. BirdVox-full-night: a dataset and benchmark for avian flight call detection, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2018.

The creation of this dataset was supported by NSF grants 1125098 (BIRDCAST) and 1633259 (BIRDVOX), a Google Faculty Award, the Leon Levy Foundation, and two anonymous donors.

Conditions of Use
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Dataset created by Vincent Lostanlen, Justin Salamon, Andrew Farnsworth, Steve Kelling, and Juan Pablo Bello.

The BirdVox-70k dataset is offered free of charge under the terms of the Creative  Commons Attribution 4.0 International (CC BY 4.0) license:
https://creativecommons.org/licenses/by/4.0/

The dataset and its contents are made available on an "as is" basis and without  warranties of any kind, including without limitation satisfactory quality and  conformity, merchantability, fitness for a particular purpose, accuracy or  completeness, or absence of errors. Subject to any liability that may not be excluded or limited by law, Cornell Lab of Ornithology is not liable for, and expressly excludes all liability for, loss or damage however and whenever caused to anyone by any use of the BirdVox-70k dataset or any part of it.

Feedback
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Please help us improve BirdVox-70k by sending your feedback to:
vincent.lostanlen@gmail.com and af27@cornell.edu

In case of a problem, please include as many details as possible.

Acknowledgements
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Jessie Barry, Ian Davies, Tom Fredericks, Jeff Gerbracht, Sara Keen, Holger Klinck, Anne Klingensmith, Ray Mack, Peter Marchetto, Ed Moore, Matt Robbins, Ken Rosenberg, and Chris Tessaglia-Hymes.

We acknowledge that the land on which the data was collected is the unceded territory of the Cayuga nation, which is part of the Haudenosaunee (Iroquois) confederacy.