GSoC’23: Integrating Apple Music with ListenBrainz

Hello everyone!

My name is Vardan and I am a student at University of Alberta. I’ve always had a thirst for knowledge and a deep desire to make contributions to projects that have a global impact. I like listening to music and the idea of contributing to an adjacent music metadata project was captivating for me. I eagerly embarked on this journey, contributed my best, and am happy to have made a meaningful impact. This experience not only aligns perfectly with my academic pursuits but also presents a chance to collaborate with some of the brightest minds in the field.

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GSoC ’23: Artist similarity graph

Hello everyone,

I am Arshdeep Singh, a 4th year CS student from the University of Manitoba. I worked as a GSoC contributor for MetaBrainz on the Artist similarity graph project. I would like to dive into the details of the project and share my experiences of the same.

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GSoC’23: Dataset Hoster Improvements

Hi Everyone!

I am Vishal Singh (also known as Pixelpenguin on IRC). This year I participated in Google Summer of Code under MetaBrainz and worked on improving MetaBrainz Dataset Hoster repository. My mentor for this project was Kartik Ohri (lucifer on IRC). This post summarizes my contributions made for this project.

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GSoC 2023: Feed Section in ListenBrainz Android

Hello everyone!

I am Jasjeet Singh (also known as jasje on IRC and 07jasjeet on GitHub). I am an undergraduate student pursuing information technology at UIET, Panjab University, Chandigarh, India. This year I participated in Google Summer of Code under MetaBrainz and worked on implementing a feed section in the new and upcoming ListenBrainz Android app derived from the ListenBrainz website. Along with the implementation of the original feed section, I have also added new features to the section that are currently available only on the app. My mentor for this project was Akshat Tiwari. (akshaaatt on IRC)

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ListenBrainz App 2.0.0: A Major Leap Forward

We are excited to announce the release of ListenBrainz 2.0.0, an update that we launched around 3 weeks ago with a lot of improvements, and bug fixes. This release saw significant contributions from community members, as well as new contributors making their debut in the ListenBrainz project.

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Redesigning ListenBrainz

Today we are pleased to present the new and improved ListenBrainz website!

Since 2019, we have been adding features and pages to the ListenBrainz website without a clear plan as to what we wanted the interface to look like.
The result is a website that is not very user friendly, with poor mobile screens support and features hidden behind menu items that are hard to discover. It’s a mess.

We have been working hard to redesign the website with those goals in mind: simplify the menu and navigation into clear sections, make it easier for users to find what they are looking for, and refresh and improve the overall look and feel of the website.

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AIBrainz Playlist Generator (beta)

MetaBrainz as an organisation has never much dabbled in (artificial) intelligence, but a number of recent factors have led to the team doing some exciting behind-the-scenes work over the last few months.

Lately more and more potential contributors have come to MeB interested in working on AI projects, and with ListenBrainz we have an excellent dataset. With a current focus on playtesting and finetuning our playlist features we also have the perfect use-case.

So, without further ado, we invite you to test the beta version of our new AI-powered playlist generator:

AI Brainz Playlist Generator (beta)

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Explore Your Year in Music 2022

ListenBrainz is excited to announce the release of your #YEARINMUSIC reports for 2022! Log in to your ListenBrainz (LB) and click here to see your report. Don’t have a LB account? See what you’re missing.

Revisit and share your top artists, albums, tracks and neighbours from last year. Topped off with oodles of interesting statistics, a browsable cover collage, and brand new playlists of songs that you may have missed that our currently-benign algorithm thinks you will love.

You made it through, and you listened to some great tunes along the way.

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