update readme

README.md

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 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 Linux.
+It is made available both as a Python library and as a command-line tool for Windows, OS X, and GNU/Linux.
 
 
 ## Installation
@@ -85,12 +85,26 @@ Below is a typical output from the test suite (file `fd79e55d-d3a3-4083-aba1-4f0
 
 ## Contact
 
-Vincent Lostanlen, Cornell Lab of Ornithology (`@lostanlen` on GitHub).
-For more information on the BirdVox project, please visit our website: [https://wp.nyu.edu/birdvox](https://wp.nyu.edu/birdvox)
+### Official website
+Please visit our website for more information on the BirdVox project: [https://wp.nyu.edu/birdvox](https://wp.nyu.edu/birdvox)
 
-Please cite the following paper when using BirdVoxDetect in your work:
+The main developer of BirdVoxDetect is Vincent Lostanlen, scientist at CNRS, the French national center for scientific research.
+
+### Discussion group
 
+For any questions or announcements related to BirdVoxDetect, please refer to our discussion group:
+[https://groups.google.com/g/birdvox](https://groups.google.com/g/birdvox)
+
+### References
+Please cite the following paper when using BirdVoxDetect in your work:
 
 **[Robust Sound Event Detection in Bioacoustic Sensor Networks](https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214168&type=printable)**<br/>
 Vincent Lostanlen, Justin Salamon, Andrew Farnsworth, Steve Kelling, and Juan Pablo Bello<br/>
 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](https://www.justinsalamon.com/uploads/4/3/9/4/4394963/cramer_taxonet_icassp_2020.pdf)**<br/>
+Jason Cramer, Vincent Lostanlen, Andrew Farnsworth, Justin Salamon, and Juan Pablo Bello<br/>
+In IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Barcelona, Spain, May 2020.