Releases: BirdVox/birdvoxdetect
1.0
This is the first release of the 1.0 series. It is identical to 0.6.0.
BirdVoxDetect is a pre-trained deep learning system which detects flight calls from songbirds in audio recordings, and retrieves the corresponding species. It relies on per-channel energy normalization (PCEN) and context-adaptive convolutional neural networks (CA-CNN) for improved robustness to background noise. It is made available both as a Python library and as a command-line tool for Windows, OS X, and GNU/Linux.
Please visit our website for more information on the BirdVox project: https://wp.nyu.edu/birdvox
The main developer of BirdVoxDetect is Vincent Lostanlen, scientist at CNRS, the French national center for scientific research.
For any questions or announcements related to BirdVoxDetect, please refer to our discussion group: https://groups.google.com/g/birdvox
Please cite the following paper when using BirdVoxDetect in your work:
Robust Sound Event Detection in Bioacoustic Sensor Networks
Vincent Lostanlen, Justin Salamon, Andrew Farnsworth, Steve Kelling, and Juan Pablo Bello
PLoS ONE 14(10): e0214168, 2019. DOI: https://doi.org/10.1371/journal.pone.0214168
As of v0.4, species classification in BirdVoxDetect relies on a taxonomical neural network (TaxoNet), which is distributed as part of the BirdVoxClassify package. For more details on TaxoNet, please refer to:
Chirping up the Right Tree: Incorporating Biological Taxonomies into Deep Bioacoustic Classifiers
Jason Cramer, Vincent Lostanlen, Andrew Farnsworth, Justin Salamon, and Juan Pablo Bello
In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.
0.6.0
This is the first stable release of the 0.6 series.
The main change with respect to the v0.5 series is the update from BirdVoxClassify v0.2 to v0.3. The species classifier is now "flat multitask" by default and includes hierarchical consistency. Furthermore, the order "Passeriforme" is now spelled in the plural: "Passeriformes". We have added various encodings for species: English name, scientific (Latin) name, and 4-letter code (#85). The "other" class is represented as an empty string. Lastly, we have truncated the number of digits of confidence in the checklist (#86).
Assets 3
0.6.0b1
This is the first beta release of the 0.6 series.
The main change with respect to the v0.5 series is the update from BirdVoxClassify v0.2 to v0.3. The species classifier is now "flat multitask" by default and includes hierarchical consistency. Furthermore, the order "Passeriforme" is now spelled in the plural: "Passeriformes". We have added various encodings for species: English name, scientific (Latin) name, and 4-letter code (#85). The "other" class is represented as an empty string. Lastly, we have truncated the number of digits of confidence in the checklist (#86).
0.6.0a5
0.6.0a4
0.6.0a3
0.6.0a2
0.6.0a1
0.6.0a0
This is the first alpha release of the 0.6 series.
The main change with respect to the v0.5 series is the update from BirdVoxClassify v0.2 to v0.3. The species classifier is now "flat multitask" by default and includes hierarchical consistency. Furthermore, the order "Passeriforme" is now spelled in the plural: "Passeriformes". We have added various encodings for species: English name, scientific (Latin) name, and 4-letter code (#85). The "other" class is represented as an empty string. Lastly, we have truncated the number of digits of confidence in the checklist (#86).
0.5.1
This is the first bugfix release of the 0.5 series.
In comparison with 0.5.0, we have changed the default classifier: it is no longer TaxoNet but "flat multitask". In doing so, we revert to the species classifier that was already present in BirdVoxDetect 0.3.0. We have made this change because we have noticed a surprisingly poor performance of TaxoNet on hold-out data. Thus, we err on the side of caution and offer a more straightforward deep learning model as the new default. We are currently investigating the cause of the problem in coordination with BirdVoxClassify developers.