A neural network framework for researchers studying acoustic communication


vak is a library that makes it easier for researchers studying animal vocalizations—such as birdsong, bat calls, and even human speech—to work with neural network algorithms.

To learn more about the goals and design of vak, please see this talk from the SciPy 2023 conference, and the associated Proceedings paper here.

Thumbnail of SciPy 2023 talk on vak

Currently, the main use is automated annotation of animal vocalizations. By annotation, we mean something like this example of annotated birdsong:


Please see links below for information on how to get started and how to use vak to apply neural network models to your data.

Getting Started

If you are new to working with vak, and you’re looking for installation instructions and a tutorial, start here.

How-to guides

If there is something specific you’re trying to do, like use your own spectrogram files or annotation formats with vak, please check in the How-to guides.

Getting Help

For help, please begin by checking out the Frequently Asked Questions (FAQs).

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:

To report a bug, or to request a feature, please use the issue tracker on GitHub:


If you need to look up information about the command-line interface, configuration files, etc., please consult the Reference.


To learn about development of vak and how you can contribute, please see Development

About vak

For more about the goals of vak and its development, please see About vak.


Not enough open-source research software libraries have poems. We do, here: Poems.