Allow me to spread the word about ListenBrainz , the occasion being that ListenBrainz is about to hit 100.000 users.
ListenBrainz is a FOSS project that aims to crowdsource listening data and release it under an open license. Basically it’s Last.fm but better. Whatever you use to listen to music, you can probably link it up with ListenBrainz. For instance you can connect Spotify, Apple Music, Soundcloud, Last.fm . You can link it up with loads of music players . If you’ve kept track of your what music you’ve listened to up to this point, don’t worry, there are several ways to import them into ListenBrainz.
All ListenBrainz listening data is available for all to use. This means that we don’t need to rely on big companies like Spotify for recommendation algorithms. We can use whatever algorithm suits us best. All sorts of other services could be build to make use of the ListenBrainz data set. The dataset can also help analyze other services’ algorithms, for instance the Fair MusE project uses LB-data and LB-users to investigate the fairness of different music service algorithms.
Obviously ListenBrainz initially suffered from being a comparatively small service, For good recommendations you need loads of data. But it’s growing every day and I feel like the 1 billion listens is an impressive milestone. And ListenBrainz has the advantage of having listening data from several services, Spotify could never recommend you music that’s not on Spotify. ListenBrainz, because it’s open, doesn’t have such inherent blindspots.
I am not working for ListenBrainz in any way, I just really like this project as well as MusicBrainz , and I like to spread the word. I think the aims of the ListenBrainz probably align with some Fediverse-folks. If you don’t care about the service itself, you could still link up to support FOSS music services, not only LB itself, but other services that are, can and will be built using LB’s data. If you use another service to store your own listening data, for instance Last.fm, you could use ListenBrainz as a backup for you data in case the other sevice ever enshittifies. Note: you shouldn’t sign up if you want your listening data to be private, that’s not what LB is for. I care very much about privacy, but in the case of LB I consciously choose to share my music listening data with others for my own benefit.
Curious to hear peoples thought on all this.
P.S. I have posted about LB over a year ago. I don’t intend to spam this service, but i feel like it could be useful for folks on here, and I think most of you folks would support the spreading of FOSS. And LBs usercount rising from 36k january last year to 100k now seemed like a good celebratory occasion to spread the love once more.
This is pretty much the step I need to get back to listening to my own music rather than streaming. Can it plugin to ‘offline’ apps?
The other way around, and yes.
https://kawaiidango.github.io/pano-scrobbler/ is one example, but most decent Desktop/Mobile applications have some sort of plugin.
Depends on the app.
If it caches the plays and syncs it back to the scrobble service?
Probably possible.
Afaik it’s not possible for Jellyfin.There was a time I used Plex with PlexAmp for music, pretty sure it kept stats
There is a Jellyfin Plugin for this. https://github.com/lyarenei/jellyfin-plugin-listenbrainz
Offline listen history playback is my issue.
I know about the plugin (lol)
(Scrobbled by Spotify and Jellyfin)
Depends. LB supports traditional Lastfm scrobling, so you can use players that scrobbles to Lastfm if you can change the URL
The in-app player is more limited, but a good old Navidrome instance is plenty enough!
So what happens to the data? As far as I can see you’re uploading your music listens to the service and you don’t have a private profile, it’s always public and everything is being provided as a download for everybody. So everybody can get the full amount of my listening history, including Metadata telling them for example when I was awake, listened to sad songs or drinking songs on a thursday night?
Yes, there is not a feature for private profiles. If your listening data is a privacy concern to you it’s better not to use LB.
I felt a bit weird about it at first, but the one thing keeping me tied to Spotify was how useful it was for discovering new music (though even that had been degrading by the time I cancelled it).
If you’re someone who either prefers to listen to music that they already know and love, or someone who enjoys discovering new music through manual effort, then Listenbrainz isn’t for you
However, if you’re currently relying on the recommendations of a service like Spotify, then it’s at least worth considering. For me, I became a lot more at ease with Listenbrainz when I realised that this kind of music recommendation simply isn’t possible without other people’s data — and that part of the “price” for being able to access recommendations built from that data is that my listening history gets added to the pool of listening data used by the recommendation system.
If it’s Spotify’s pool that I’m contributing to, then I feel like I’m getting a pretty bad deal, because they hoard that data like a digital dragon, and then use it to further entrench their monopolistic position in the market. I don’t like that — it makes me feel complicit in the grossness.
Whereas with Listenbrainz, I’m contributing to a data commons of sorts. Listenbrainz’s recommendation algorithm has gotten so much better in the couple of years that I’ve been using it, and that wouldn’t be possible without a growing pool of data. Independent researchers and developers are able to benefit from it, and the more people we have making stuff in this space, the more we chip away at Spotify’s power.
Like I said, having my data be so public does make me feel a tad uneasy, but with data like this, it tends to only be valuable in bulk (meaning the system doesn’t care about any individual’s sad drinking songs), or hypothetically, to individuals who are excessively concerned with another individual (such as stalkers, I guess). However, that last point doesn’t concern me, because I made my Listenbrainz account under a username that’s unconnected to any of my others, and my profile shows no indication of who I am on Spotify.
I’m sure that someone dedicated and skilled enough could retrieve my Spotify account name from the system, because I linked my account way back when I did have Spotify, but I trust Listenbrainz with my data a hell of a lot more than I do Spotify. Spotify definitely have way more money to hire cybersecurity folk to prevent exfiltration of user data, but they’re so opaque that even if there were a breach, I wouldn’t trust them to tell me. I’ve been following Listenbrainz’s development for a while, and they’re pretty cautious and transparent with how they go about things.
To be clear, I’m not formally affiliated with Listenbrainz in any way. I have contributed to improving documentation a few times (because that’s usually the best way I can support open source projects, as a mediocre programmer), but that stems from the same thing that made me write this comment: I just really like what they’re trying to do, and I think the world would be a little better if more people joined it. (also, I am just a huge nerd for metadata schema, and the affiliated musicbrainz project has so much cool stuff for me to learn about)
Yeah, I think one issue is how this aggregate data is being provided for download. Is it really “this user has listened to this song on this day at this minute”, or is it kind of an aggregate data like “users who listen to Metallica also listen to Pantera” and “the most listened song for Taylor Swift is shake it off”?
Yes I think it is like you describe.
Here is someone from MetaBrainz explaining why.
Such a great service.
Both it and musicbrainz.Can someone explain to a Gen x guy what “listening data” gets me? I’ve been living off a folder of mp3s for 30 years. Does this use my music? Does this get it from the Internet somewhere? How is it different from asking Alexa to play music for me? Thanks.
I’ve been using LastFM for nearly two decades now. First of all, having personal listening statistics is kind of fun. It might be not for everybody, but it’s nice to see which albums are your most played over a year or what you listened to back in 2015, how your favorite artists changed, which album really vibed with you and so on.
Second, you can get really good recommendations for new music when you have a larger user base and are running into a smaller genres. So just like Amazon’s and people who bought this product also bought that product for music. So people who listen to Britney Spiels also like to listen to Christina Aguilera. That might be obvious for you, but it’s totally interesting if you go down some of these genres and if you want to explore them.
And on a broader scale, listening data is quite valuable to create a good music service. So if somebody never heard of a band called Deep Purple and wants to change that, there might be this one song everybody knows from Deep Purple. And this is, of course, the most popular, but how do you find out that this is the most popular? So if you have your own Jellyfin installation, you load in several albums of Deep Purple, but you need some data source to tell you that ‘smoke on the water’ is that famous song from Deep Purple that everybody’s listening to.
I’ve been living off a folder of mp3s for 30 years.
Same here. I love that shit. My mood is the algorithm. I still occasionally get new stuff, but from other sources I happen to see or hear, like a Netflix show that has it in the background or a musician’s personal recommendation in an interview, and I go look it up manually. But even if I never got anything new, I already have more music than I could easily listen to in a lifetime that I already know I liked at least once.
I’ve tried streaming sources, but it never hits right. This way, where I am specifically picking the artist or album, it’s always right, always fresh, and I’m always listening to something I want to hear.
It depends on your preferences, but myself I just like knowing what I listen to a lot and send my monthly cover art collage to brag about my blorbos
The player / radio are nice, but I personally created my own radio generator based on my data
Been an LB user for more than 2 years now, and it’s been my nerd snipping since then. The metadata is a joy to work with, and it’s quite easy to script things.
It does have that “brand new app” smell to it, but that means you get to experience seeing a long awaited feature finally getting done.
Used Last.fm for like 3 months before finding out about ListenBrainz and making the switch. Truly amazing app, love all of their services (Picard my goat) and I’m happy to hear more people are joining!
I wish the social aspect was a bit more active though, I always follow people with similar taste but I never get a follow back (and the accounts always have 0 people they follow). Also I never see pinned songs and such :(
Yeah, it’s pretty low on the social side of things. However, having watched the massive progress the project has made over the last few years makes me hopeful that it’ll continue to improve. They seem to be quite smart about how they go about developing new features, which is wise for an open source project. It’s been pretty cool to watch how good their recommendation algorithm has been getting though, compared to when I first joined
I agree on the social aspect lacking a bit. But who knows, ListenBrainz got better and better over the past years, perhaps with more users there will be more demand for social functionalities aswell, and perhaps they’ll be implemented in the future. LB was very rudimentary when I signed up, it’s nice seeing it grow and improve.
Listenbrqinz seems to keep prioritizing the discovery aspect rather than the stats
Thanks for the tip, will check it out. The only things that bugs me it that there source code is only on Microsoft Github service, just self-host forgejo like sane FOSS projects do
Thank you for the reminder! Donated today. Such a great service
“Give us more data so we can take any of the effort out of deciding what to like.” is a big miss for me.
I’ll happily take my 30 minutes of scrolling Bandcamp and YouTube at bedtime for new artists if it means that my preferences and habits are none of your fucking business.
Fair enough, personally I don’t mind using algorithms as long as they are fully transparent
Meta said at the outset that they were fully transparent.
Pass on further delegating my brain to a machine.
MetaBrainz is a non-profit dedicated to open-source and open-data. So if people don’t like the algorithms LB has integrated, they can just build their own.
About not delegating your brain to machines, that’s a fair point, and I would encourage people to consciously choose where to use machines and where to use their brain. If you enjoy searching for music, it would be foolish to delegate it to a machine. For me personally though it’s usefull, using an algorith here allows me to spend energy on other things that are equally stimulating for my brain. I particularly like LBs ‘fresh releases’ feature, which gives you heads up about new releases by artists that you’ve listened to.
“About not delegating your brain to machines, that’s a fair point, and I would encourage people to consciously choose where to use machines and where to use their brain”
Yeah, big agree on this front. We should be using technology as a tool to aid us to do the stuff we care about, rather than letting ourselves be made subordinate to the tech itself. For some people, that kind of agency means using an open source system like Listenbrainz, and for some, like the person you’re replying to, that means continuing to discover music in their own way. Both of these approaches are fine — indeed, the whole point of building tech that serves as tools is that if our experience tells us that we have a task that wouldn’t benefit from the tool, we can just leave it in the box.
Personally, I enjoy going for a combination approach — I sometimes use listenbrainz as a catalyst to help me discover new stuff beyond my experience, but once I have a few new artists I’m interested in, I then go and do some manual digging around them. I don’t need to do this manual work part of it, but it’s a key part of my enjoyment of the music discovery process — so I can somewhat relate to the person you’re replying to’s preference
I already use MusicBrainz Picard to scan and sort my music files.
Doesn’t look like it has Plex support?
- Eavesdrop.FM, submits Plex music listening data to ListenBrainz
- phooks, a python script that submits local Plex listens using web hooks and file lookups
Thanks!
ListenBrainz
I saw that as well so I have left Plex scrobing to Last.FM, then Listenbrainz can pull the data from there.
If there is a plugin, everything is (sort of) supported.
Jellyfin has a listenbrainz plugin.
Looks interesting, any suggestions about how to get started? Is there a mobile app I can use to play songs?
EDIT: There is a mobile app that automatically tracks what music you’re playing (Link), it works quite well.
As someone who only cares about the stats and social features , i still do not see what listenbrainz has over lastfm
- Listenbrainz isn’t owned by David Ellison.
- Do I need a #2?
Do I need a #2?
Yes. People cares about features they are interested in , not who own it
Better track matching
More stats visualizations
Cover art collages of your favourite tracks
Fresh releases of you favourite artists
And a fully open dataset
Whatever you use to listen to music
Winamp gang! (sadly not supported)
But I don’t want my listening history publicly accessible (I was an avid Last.fm user in the '10s, but always kept my profile private), so I would skip this one anyway. Love MusicBrainz though.
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