Try Pandora - been using it since very early days. It's the only service I've ever used that has consistently produced playlists I enjoy based often on just a couple of thumbs ups/thumbs downs.
The lie of music discovery algorithms
111–120 of 198 posts
Re: The lie of music discovery algorithms
#112Earlier quoted context omitted.
I don't work at Spotify anymore and I didn't work on the tech I'm describing, but I picked up a bit about what was going on while there. First, there is/was no single algorithm, but the core ideas driving a lot of recommendations is: 1. Create user taste vectors 2. Match those vectors to other users or collections of tracks 3. Use that information and combinations of other things to find recommendations. Each step of…
So collaborative filtering?
Collaborative filtering is similar but for huge recommender systems they’re not going to create a huge MxN matrix where M is users and N is items. I think what they’re referring to would be called a “two tower” model where you have a learned vector for the user, a learned vector for the song, and the cosine similarity is their affinity. It’s pretty performant because you can cache the song vectors.
Re: The lie of music discovery algorithms
#113No music discovery algorithm has satisfied me. All data-driven approaches make predictions based on historical data. Personally I enjoy being exposed to entirely new genres and sounds I've never heard before, instead of variations on genres I've listened to a lot. My solution: listening to NTS, an eclectic online radio station, where diverse artists create playlists.
I agree that NTS radio is one of the best ways to be exposed to interesting new and old music, obscure stuff, brilliant mixes, etc.
The NTS app is great: for Web, Android, iOS - it's always being steadily improved. A very nice feature to aid discovery/curation is that every track in a tracklist has a 'copy song and artist info' so you can easily search for tracks on your streaming platform. Not sure if this is a subscriber only feature.
I also use the 'identify song' feature in the Google search app on my phone, similar to Shazam.
If the algorithms aren't doing it for you then do yourself a favor and head to https://nts.live
Re: The lie of music discovery algorithms
#114This is great to hear, though I'm curious why photos on your phone / pinterest would be relevant to a recommendation system? Surely the biggest signal would be what Spotify already uses: the features of various relevant factors (your previous listening sessions, your current session, what other similar sessions look like, etc.), that said, their recommendation system is surprisingly terrible given how much easier mus…
YouTube’s algorithm isn’t very good for users because it doesn’t really separate mildly interesting videos that you finish from awesome content you loved. YouTube of course doesn’t care because they don’t make more money when you see something awesome.
It does distinguish between videos you thumbed-up (or down) vs. videos you merely played. At least that works for me with YouTube Premium/Music.
Re: The lie of music discovery algorithms
#115The two issues I've had with every discovery algorithm: "We have [favorite band] at home" - it picks things you like from your favorite band - instruments, tempo, etc then finds bad knockoffs that are superficially similar but painful to listen to. The "Iron and Wine" problem - some bands are so generic that they tick every single similar box and flood your recommendations. For years, it didn't matter what band/genre…
> it picks things you like from your favorite band - instruments, tempo, etc then finds bad knockoffs that are superficially similar but painful to listen to.
This is pretty bad if you have strong feelings about how much screaming a metal song should have. There are songs that fit exactly what I like except for that variable and Spotify does not get that I keep skipping them for a reason. It's rarely a "bad knockoff", but it definitely hits "painful to listen to".
It's really strange to me since it successfully creates playlists around different types of music that are sort of similar but shouldn't cluster together.
Re: The lie of music discovery algorithms
#116> They are not suggesting new, very interesting melodies. They are finding you the tweaked versions of the songs you already like and, even on your first listen you can predict the melody that’s to come This seems like the complaint of somebody who hasn't been using spotify very long. After a decade plus, I feel like my algorithm is a rich compost pile of all of my previous phases of music. Spotify is excellent at le…
I feel the opposite: my Spotify recs (after at least 8 years with an account) tend to get stuck on whatever I've been listening to recently. I've had to consistently go afield to find any new (to me) music. Even their "new releases for you" falls short of recommending me releases from artists I follow. How much less capable could it be?
Release Radar is consistently the worst feature of Spotify. It misses entire new albums from artists I listen to regularly, and seems to have a quota of songs to fill so after the first two or three it's no longer aligned with my interests. I can forgive it not being coherent since it's supposed to include multiple genres together, but I can't forgive it going way off from what I like just to hit 30 songs.
Re: The lie of music discovery algorithms
#117In the age of internet, engagement optimization and recommendation algorithms create a new way that we are affected by the behaviour of others. That annoying dark pattern on a piece of software you use? Because there are people who fall to it, clicking on an ad or "engaging" more. That stupid show that keeps being recommended to you? Because a lot of people just sit on the couch, watching something on the list that d…
The same for me. Nowadays i make my own songs using Udio and i upload 'em to YT. It is unlikely i will ever listen to suggested songs ever again, by any service.
Re: The lie of music discovery algorithms
#118Earlier quoted context omitted.
Yess! Thank you for commenting. I am very interested in this topic. Please do share with me if you find any interesting ways to explore new music for your taste
local record store. talk to the people who work there, tell them the 5 albums you’ve been hooked on lately. at the end of the day no matter how many times we beat our heads into the same wall, we’re not even close to an accurate discovery model, music nerds are far better at recommendations than any discovery models. far better. don’t let their insufferability discourage you. you will be too once you start diving int…
> local record store. talk to the people who work there, tell them the 5 albums you’ve been hooked on lately.
Unless your interests are niche. A fun game I used to play as a teen was going with my parents to the record store and seeing if they had any music I listened to online while my parents shopped. Never found a single CD (but they couldn't be that niche, this story is about bands I found out about from my friends at school!). Employees tried to be helpful, but there's only so much they can do when someone comes in and asks for a list of bands they've never heard of.
Re: The lie of music discovery algorithms
#119Way back when Last.FM has its own radio service, I could throw a few random genres and/or artists at it, and it would recommend me pretty much exactly want I wanted every time. I gladly enabled scrobbling in my music players, and it tended to recommend me good stuff every time. Ever since its radio feature got killed, its database has been getting worse and worse. Just now, I tried to search for some things it used to be good at finding, and the artists section was not filled with artists at all, but rather a bunch of what appear to be random playlists with incomplete metadata.
Pandora had decent algorithms for recommending things, but it had such a small library that it would frequently repeat the same handful of albums for anything I searched for. This irks me, as I hate wearing out good music.
Spotify is currently where I keep my weeks-long playlists that I've built over the past couple decades. Even with such large playlists as input for their radio recommendations, Spotify doesn't do a very good job recommending new music either.
Whatever happened to the good databases and their algorithms? They definitely used to exist.
Re: The lie of music discovery algorithms
#120Here's something rather mundane, but definitely works for me: open Internet Archive's Audio section and choose "This Just In". Click on the first interesting thing you see and let it play. Most things I choose are pretty good to so-so, but sometimes I find a real gem (e.g., 3-hour-long John Peel radio captures transferred from cassette from the late 1970s).
It's all rather random but relies somewhat on your gut instinct. I find it more enjoyable than the top music streaming services. Case in point: someone uploaded an excellent field recording of a Bruce Hornsby concert from 2017 yesterday - listened to the whole thing a few times already (and I'm not really a big fan, but he's a great showman).