Meet our GSoC 2022 Contributor

Audacity is taking part in Google Summer of Code 2022 and this year we’re joined by a contributor on one project:

Waveform Rulers

This project will add the ability to display a logarithmic ruler for amplitude (measured in decibels) while still drawing the waveform according to a linear scale. This is useful because linear waveform graphs are more intuitive than logarithmic graphs, but audio engineers are accustomed to using decibel units to cover the wide range of amplitudes perceptible to humans. The GSoC project will also modify the timeline ruler, adding the option to use the musical units of beats and measures instead of the regular units of hours, minutes and seconds.

Contributor: Michael Papadopoulos
Mentor: Paul Licameli

You can learn more about Michael’s project by reading his introductory blog post and by following his weekly blog for regular progress updates.

Join Audacity for GSoC 2022!

We are delighted to announce that Audacity is participating as an open source organization in Google Summer of Code (GSoC) 2022. For those who are unaware, GSoC is an annual program where new contributors are paid a stipend by Google to write code for various organizations in open source.

Google Summer of Code logo
Google Summer of Code

Last year, two highly talented students successfully completed projects with us here at Audacity. This year, you don’t have to be a student to take part (students are still welcome though!) and there are a few other changes that potential candidates need to be aware of. Please see this page for more information about the program and how to apply to join Audacity as a GSoC contributor.

GSoC 2021 Success!

This week marked the end of the Google Summer of Code (GSoC) program for 2021, which saw over 1200 students work on over 200 open source projects. This year, 2 students joined us at Audacity, and we are happy to report that both completed their projects successfully! The projects were as follows:

Source Separation

Hugo Flores Garcia, mentored by Dmitry Vedenko, implemented a deep learning AI tool that, given an appropriately trained model, is able to take an audio track with multiple sound sources (e.g. a combined “singer + piano” track) and splits it into multiple tracks, with one track for each source (i.e. a “singer” track and a “piano” track). This opens up a whole variety of interesting use cases, including karaoke and background noise removal. You can learn more about the Source Separation project in Hugo’s blog.

Spectral Editing

Edward Hui, mentored by Paul Licameli, implemented the ability to edit audio tracks by drawing on the spectogram rather than the waveform as is usually the case in Audacity. He also implemented smart selection tools to automatically select regions of contiguous “colour” on the spectogram, and to select overtones (harmonics) in addition to the fundamental frequency. Spectral editing is useful for removing unwanted sounds and background noises without distorting the main part of the audio signal. You can learn more about the Spectral Editing project in Edward’s blog.

Next steps

We will continue to work with the students over the coming weeks to make the final touches necessary to get their code merged into the program, at which point it will become available in GitHub Actions builds of the master branch and a subsequent stable release of Audacity.