vak
is a Python library for bioacoustic researchers studying animal vocalizations such as birdsong, bat calls, and even human speech.
The library has two main goals:
- Make it easier for researchers studying animal vocalizations to apply neural network algorithms to their data
- Provide a common framework that will facilitate benchmarking neural network algorithms on tasks related to animal vocalizations
Currently, the main use is an automatic annotation of vocalizations and other animal sounds. By annotation, we mean something like the example of annotated birdsong shown below:
You give vak
training data in the form of audio or spectrogram files with annotations,
and then vak
helps you train neural network models
and use the trained models to predict annotations for new files.
We developed vak
to benchmark a neural network model we call tweetynet
.
Please see the eLife article here: https://elifesciences.org/articles/63853
Short version:
$ pip install vak
$ conda install vak -c pytorch -c conda-forge
$ # ^ notice additional channel!
Notice that for conda
you specify two channels,
and that the pytorch
channel should come first,
so it takes priority when installing the dependencies pytorch
and torchvision
.
For more details, please see: https://vak.readthedocs.io/en/latest/get_started/installation.html
We test vak
on Ubuntu and MacOS. We have run on Windows and
know of other users successfully running vak
on that operating system,
but installation on Windows may require some troubleshooting.
A good place to start is by searching the issues.
Currently the easiest way to work with vak
is through the command line.
You run it with configuration files, using one of a handful of commands.
For more details, please see the "autoannotate" tutorial here:
https://vak.readthedocs.io/en/latest/get_started/autoannotate.html
Please see the How-To Guides in the documentation here: https://vak.readthedocs.io/en/latest/howto/index.html faq.html#faq
For help, please begin by checking out the Frequently Asked Questions:
https://vak.readthedocs.io/en/latest/faq.html.
To ask a question about vak, discuss its development,
or share how you are using it,
please start a new "Q&A" topic on the VocalPy forum
with the vak tag:
https://forum.vocalpy.org/
To report a bug, or to request a feature,
please use the issue tracker on GitHub:
https://github.com/vocalpy/vak/issues
For a guide on how you can contribute to vak
, please see:
https://vak.readthedocs.io/en/latest/development/index.html
If you use vak for a publication, please cite its DOI:
is here.
For more on the history of vak
please see: https://vak.readthedocs.io/en/latest/reference/about.html
It has only three letters, so it is quick to type, and it wasn't taken on pypi yet. Also I guess it has something to do with speech. "vak" rhymes with "squawk" and "talk".
Thanks goes to these wonderful people (emoji key):
This project follows the all-contributors specification. Contributions of any kind welcome!