Summer of Code: But wait, we have another participant!

This year’s Google Summer of Code participant selection process created a situation that we’ve never encountered before: Two participants put in excellent proposals for the same project and both participants did a very good job of engaging with the community. But there was one difference between the two — one participant had engaged with us months earlier, written a whole new feature, saw it through the release process and got the feature into production.

This compelled us to accept the participant with whom we had already built a rapport. But collectively we felt really really bad about the fact that the other participant, Chinmay Kunkikar, would be rejected from Summer of Code and not work with us.

Fortunately we had recently earned 15,000GBP from our participation in the ODI Peer Learning Network 2, which we decided to spent on contributions to Open Source and musicians that our team loves. When the suggestion came up that we could create an internship on the spot that more or less follows the concept of Summer of Code, and that we could take on Chinmay and knock out yet another project during the summer, we jumped on the idea.

And with that I am pleased to announce that Chinmay will take on the “Upcoming and new releases page” project for ListenBrainz. This project will show a timeline of upcoming music releases and releases that have been recently released, complete with the ability to play these releases in the page.

Our team feels strongly about Chinmay as well as this new feature, so we’re excited that we’re taking on this 8th participant for this summer.

Welcome Chinmay!

Welcoming GSoC 2022 students!

Thank you to everyone who submitted a proposal to MetaBrainz for this year’s Summer of Code!

This year, we have selected seven projects. The chosen students and projects are:

Ansh Goyal – BookBrainz and CritiqueBrainz: CritiqueBrainz reviews for BookBrainz entities

Ashutosh Aswal – MusicBrainz Android App: Adding BrainzPlayer in Android App

Prathamesh Ghatole – ListenBrainz: Clean Up The Music Listening Histories Dataset

Shatabarto – ListenBrainz: Send a track to another user as a personal recommendation

Shubh – BookBrainz: Unified Creation Form

skelly37 – Picard: Make Picard work in single instance mode, then improve existing error handling and crash info.

Yuzie – ListenBrainz: Add Timezone support to ListenBrainz

Welcome aboard and congratulations!
Your contributions to MetaBrainz projects and the community are impressive and admirable. We look forward to work with you over the summer and see your work come to fruition šŸ™‚

Communication is the key to success in a closely knit community as ours. Always feel free to reach out to your mentors and other members of the community if you face any issues (stuck in your code, health or family emergencies, etc.). We, the mentors, are here to support and help you.

For all the students that applied but did not get accepted: we appreciate your applications, and even if you did not make the cut this year, we hope that you will stick around and apply with us again next year when we know you better – and you know us better.

akshaaatt, alastair, lucifer, mayhem, monkey, outsidecontext, zas

MusicBrainz App 2021 Updates

Greetings, Everyone!

2021 has been a great year for the MusicBrainz Android App. The app has received updates regularly throughout the year!

Now that we are very close to 10,000+ users on the Playstore, it is evident that the app caters to the needs of a number of users, which is wonderful!

We have plans to introduce new features, involving those of ListenBrainz and CritiqueBrainz in the app. We are confident that the app serves its purpose of introducing everyone to the MetaBrainz world very soundly.

The app now features both a light and dark mode for the users!

Notable feature updates made this year can be found at https://blog.metabrainz.org/2021/07/30/musicbrainz-app/

During the end of the year, we have made some remarkable technical updates to the codebase by introducing Fastlane to the app. This eases the process for the developers and allows us to make a release with the click of a button. This means now we can have a production release every month, day, or hour.

Although going strong and steady, the MusicBrainz developers would love more contributors to join in and share their knowledge with us, while we dive deep into the world of music.

Play Store: MusicBrainz ā€“ Apps on Google Play

F-Droid: MusicBrainz | F-Droid ā€“ Free and Open Source Android App Repository

Github: metabrainz/musicbrainz-android

Thank you!

Acoustic similarity in AcousticBrainz

We’re pleased to announce that we have just released acoustic similarity in AcousticBrainz. Acoustic similarity is a technique to automatically identify which recordings sound similar to other recordings, using only the recordings themselves, and not any additional metadata. This feature is available via the AcousticBrainz API and the AcousticBrainz website, from any recording page. General documentation on acoustic similarity is available at https://acousticbrainz.readthedocs.io/similarity.html.

This feature is based on work started by Philip Tovstogan at the Music Technology Group, the research group that provides the essentia feature extractor that powers AcousticBrainz. The work was continued by Aidan Lawford-Wickham during Summer of Code 2019. Thanks Philip and Aidan for your work!

From the recording view on AcousticBrainz, you can choose to see similar recordings and choose which similarity metric you want to use. Then, a list of recordings similar to the initial recording will be shown.

These metrics are based on different musical features that the AcousticBrainz feature extractor identifies in the audio file. Some of these features are related to timbral characteristics (generally, what something sounds like), Rhythmic (related to tempo or perceived pulses), or AcousticBrainz’s high-level features (hybrid features that use our machine learning system to identify features such as genre, mood, or instrumentation).

One thing that we can immediately see in these results is that the same recording appears many times. This is because AcousticBrainz stores multiple different submissions for the same MBID, and will sometimes get submissions for the same recording with different MBIDs if the data in MusicBrainz is like this. This is actually really interesting! It shows us that we are successfully identifying that two different submissions in AcousticBrainz as being the same using only acoustic information and no metadata. Using the API you can ask to remove these duplicated MBIDs from the results, and we have some future plans to use MusicBrainz metadata to filter more of these results when needed.

What’s next?

We haven’t yet performed a thorough evaluation of the quality of these similarity results. We’d like people to use them and give us feedback on what they think. In the future we may look at performing some user studies in order to see if some specific features tend to give results that people consider “more” similar than others. AcousticBrainz has a number of additional features in our database, and we’d like to experiment with these to see if they can be used as similarity metrics as well.

The fact that we can identify the same recording as being similar even when the MusicBrainz ID is different is interesting. It could be useful to use this similarity to identify when two recordings could be merged in MusicBrainz.

The data files used for this similarity are stand-alone, and can be used without additional data from AcousticBrainz or MusicBrainz. We’re looking at ways that we can make these data files downloadable so that developers can use them without having to query the AcousticBrainz API. If you think that you might be interested in this, let us know!

Congratulations GSoC 2021 students!

Congratulations and thank you to everyone who submitted a project with MetaBrainz for this year’s Summer of Code!

This year, the selected projects are:

Ritiek Malhotra
MusicBrainz – Complete Rust binding for the MusicBrainz API

Akash Gupta
BookBrainz – Implement a “Series” entity

Akshat Tiwari
Musicbrainz Android App – Dawn of Showdown

Jason Dao
ListenBrainz –  Pin Tracks & Review Tracks Through CritiqueBrainz

Yang Yang
MusicBrainz – Push the URL relationship editor to the next level

Welcome to the team, and congratulations!
In these troubled times it is all the more impressive that you all mustered the focus and determination to work on proposals, contribute to MetaBrainz projects and integrate with the community.

In our small and tightly knit team and community, communication is key!
If you run into any kind of issue (stuck in your code, starting a part-time job, health or family emergencies, etc.) don’t hesitate to contact your mentor as early as possible to find a solution; we’re here to support you.

We mentors all look forward to working with you before, during and after the summer, guiding you to success and helping you learn and improve your skills!

ruaok, yvanzo, mr_monkey, lucifer and oknozor

Thank you for your continued support, Google!

We’ve recently received our annual $30,000 support from Google. The brings the total amount donated by Google’s Open Source Programs Office to us to over $470,000 — hopefully next year we’ll cross the half million dollar threshold!

I can’t quite express my gratitude for this level of support! Without Google’s help, especially early on, MetaBrainz may never have made it to sustainability. Google has helped us in a number of ways, including Google Code-In and Summer of Code — all of these forms of support have shaped our organization quite heavily over the past 15 or so years.

Thank you to Google and everyone at the Google Open Source Programs Office — we truly appreciate your support over the years!

Please nominate us for the Open Publishing Awards!

We’ve recently found out about the Open Publishing Awards::

The goal of the inaugural Open Publishing Awards is to promote and celebrate a wide variety of open projects in Publishing.

All content types emanating from the Publishing sector are eligible including Open Access articles, open monographs, Open Educational Resource Materials, open data, open textbooks etc.

Open data? That’s us! We’ve got a pile of it and if you like the work we do, why not nominate us for an award?

Thanks!

Google donates $10,000 in cloud computing credits. Thank you!

The Google Open Source Programs Office continues to support MetaBrainz in a number of ways and most recently they donated $10,000 in credit toward their cloud services. Thank you Google!

This credit allows us to run some services in the cloud to round out primary hosting setup — this gives us a some redundancy and allows us to not keep all of our critical eggs in one basket. We can also give our open source developers Virtual Machines from time to time, since a lot of our projects are very data heavy. Having access to a fat VM can sometimes turn a really frustrating project that makes your laptop melt into a project that is satisfying to watch chug along.

Thank you again, Google, the Open Source Programs Office and in particular, Cat Allman!

MusicBrainz Schema change upgrade downtime: 17:00 UTC (10am PST, 1pm EST, 19:00CEST)

Hi!

At 17:00 UTC (10am PST, 1pm EST, 19:00CEST) we will start the process of our schema change release. The exact time that we plan to start the change will depend on how long it takes to finish our preparations, but we expect it to be shortly after 17:00UTC.

Once we start the process we will put a banner notification on musicbrainz.org and we will also post updates to the @MusicBrainz twitter account, so follow us there for more details.

After the release is complete, we will post instructions here on how to upgrade your replicated MusicBrainz instances.

Picard 2.0 beta3 announcement

Hello people,

Thank you so much for reporting bugs in ourĀ Picard 2.0.0beta2Ā release. We fixed most of the critical bugs that you guys and gals reported. You can find the beta3 release with the fixes here – Picard 2.0.0.beta3

If you have been following ourĀ Picard related blogs, you will know that we decided to release aĀ new stable version of Picard before the beginning of the summer.

To help us, advanced users, translators and developers are encouraged to:

Note – If any of you are seasoned Windows/macOS devs and have experience with PyInstaller, we need some help with PICARD-1216 andĀ PICARD-1217. We also need some help with code signing Picard for OSX.Ā Hit us up on #metabrainz on freenode for more information. We will be very grateful for any help that you may offer!

A simplified list of changes made since 1.4 can be readĀ here.

Be aware that downgrading from 2.0 to 1.4 may lead to configuration compatibility issues ā€“ ensure that you have saved your Picard configuration before using 2.0 if you intend to go back to 1.4.