8 ms·

The lie of music discovery algorithms

• DrinkWater 2y ago
  I don’t see any connection at all between my photos and the music I listen to. This seems really, really random. Plus, there is no real explanation on the page as to how this would work, not even from a high level.
  • zeynepevecen 2y ago
    The setup is pretty basic. I've built a NextJS app, for the LLM model I am using open AI gpt-4-turbo and sending the images there directly without any database for images. I did a little prompting to get the same output everytime and when I get the output I make search on the Spotify API, find the songs and create the playlist with them on your own authenticated spotify account. Likewise I also don't have a database for the emails eighter. I am using spotifys authentication
• HellDunkel 2y ago
  Finding music requires effort and energy. I rember going to the recordshop an listening to a pile of records. After 45 minutes i would have to leave and take what i found until then becaue i was exhausted. This doesnt change with music streaming. It still takes effort to discover and process and the machine cant do that for you no matter how clever the AI. Listening to new music, filtering, seeing what is in it for you is communication and as all communication basically boils down to a biological process that can reward you with dopamine or not but will require energy either way.
• msla 2y ago
  This is a blank page.
• wasteduniverse 2y ago
  [dead]
• jerrygoyal 2y ago
  how does it technically work?
  • counterpartyrsk 2y ago
    Looks like OP is harvesting emails more than sharing their (completed) work based on this and their other project https://www.zeynepevecen.dev/ https://www.zeynepevecen.dev/
    • zeynepevecen 2y ago
      Nope my website is way out of date, sorry :) will remove that section entirely
  • zeynepevecen 2y ago
    The setup is pretty basic. I've built a NextJS app, for the LLM model I am using open AI gpt-4-turbo and sending the images there directly without any database for images. I did a little prompting to get the same output everytime and when I get the output I make search on the Spotify API, find the songs and create the playlist with them on your own authenticated spotify account. Likewise I also don't have a database for the emails eighter. I am using spotifys authentication
    • bionhoward 2y ago
      To keep your options open, it might be worth switching from GPT to either Gemini or Llama as OpenAI official policies prevent you from training on your logs with the argument this training is “illegal, harmful, or abusive,” so you’d never be able to fine tune or train your own AI in the future on your data or help others do the same. If being permanently locked into a single intelligence service (or risking getting cut off or sued) is unacceptable for you as for me then OpenAI terms today are not acceptable. Yeah yeah maybe they won’t go after you, but why miss the opportunity for malicious compliance? Ditto Claude. Try a specialized model for your use case instead. Gemini has no such customer noncompete, and with llama 3.1 meta removed theirs last week.
• BillFranklin 2y ago
  This 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 music recommendations must be versus video, yet YouTube seems to have had this nailed for 15+ years whereas Spotify's "Discover Weekly" is so bad. > I come up with an idea of generating playlists from images. Images that you shot on your phone yourself, or that you found on Pinterest, or a painting that you really like and feel inspired by. This is genuinely interesting! Do you send the images to an LLM with a prompt like "generate a list of songs that would go well with this"?
  • zeynepevecen 2y ago
    Thank you! I should check youtube's algorithm too. Yes, I have a prompt like that the current prompt is this: 'You match the vibes of the pictures with the right songs and turn them into a 3 song playlist with a playlist name. The music genre of the playlist should be consistent for each song. Be creative with music selections, explore different music, be consistent in terms of the genre of the 3 songs. The playlists should be provided in an object array format, like this: \'[{playlistName: "string", songs: [{songName: "string", artist: "string"}, {songName: "string", artist: "string"}, {songName: "string", artist: "string"}]}]\'. Do not add any other text information and only give outputs in the provided format. Your playlists must match the visual vibes and maintain the specified format without any additional information.', Pretty basic, as i said before this was only ment for me and to explore this idea, but i loved it so I wanted to share :)
  • Retric 2y ago
    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.
    • HPsquared 2y ago
• ErigmolCt 2y ago
  Music has so much power over people!
  • gnulinux 2y ago
    Unfortunately it's an extremely unprofitable industry, with very little revenue in general, and that little revenue shared by a few duopolists. Although it's an art, it's capitalistically treated like a craft, successful practitioners serving the same, safe, "good-enough", risk-free, pleasant sound again and again. I like offensive, avant-garde, creative, novel, strange music and (1) artists I love live in immense poverty (i.e. artist life) (2) even though this is the biggest passion of my in life and I think I do have some skills, working on music is 99.999...% surefire way to have financial hardship.
• sor1nmarkov 2y ago
  [flagged]
  • another-dave 2y ago
    I don't think he wants a passport photo, just saying any picture as a seed — just enter a photo of a dog (so long as it's not your "first pet" with a personalised name tag round her neck)
    • sor1nmarkov 2y ago
      Oh you are right I was being literal not sarcastic
• bsenftner 2y ago
  Music discovery has never worked for me, for the simple reason it's the lyrics, not the music. I listen to anyone speaking truth, (the truth I believe, of course), and that gives me a wide disjoint range of music, but they are all singing about political social truths. Marvin Gaye, Public Enemy, Rage Against The Machine, Beyonce, The Stranglers, The Jam, Psychic TV... It's the lyrics, and now today, we finally have the ability to have music discovery with the lyrics, with the intellectual content of the music and not just the dressing.
  • zeynepevecen 2y ago
    That's a very good point, I also love discovering with lyrics. What I tried to do is to find some connections between the image and music, maybe some connection we as humans cannot see right away.
    • bsenftner 2y ago
      I've been wondering how well a word2vec on song lyrics would work; just completely ignore the music and pair up subject matters.
  • galangalalgol 2y ago
    I only pay attention to melodies and rarely can even discern the lyrics unless I have them written out as I listen. Even relatively clean vocals like Johnny Cash just wash over me without being understood. The words for me become just another instrument that can play notes. If I can always predict the next series it is boring, if I never can, it is too challenging. In the middle I get dopamine whether I predict the notes or not. The right series of notes can make me feel such varied emotions with no words necessary. Music discovery used to work for me with pandora, nothing else has. I have no idea if they had better algorithms, or just a better catalog. It doesn't seem to work as well as it once did either. Tl;dr I don't think it is simply your preference for lyrical content over melodic content that causes the algorithms to fail. They are just bad.
  • narski 2y ago
    You might like folk punk - check out Pat the Bunny. I feel like there are two kinds of singers - people who are good at singing, and people who have something to sing about. You and I, I think, prefer the latter.
• zeynepevecen 2y ago
  Many of you asked how it looks, how it works. I've added a video under the blog post, showing how it works. Many of you were also interested in knowing what's going on behind the scenes. The setup is pretty basic. I've built a NextJS app, for the LLM model I am using open AI gpt-4-turbo and sending the images there directly without any database for images. I did a little prompting to get the same output everytime and when I get the output I make search on the Spotify API, find the songs and create the playlist with them on your own authenticated spotify account. Likewise I also don't have a database for the emails eighter. I am using spotifys authentication. As I said before this was just for me at first but it is very exticing to see many people interested by this idea. If you don't trust openAI models and don't wanna send any pic data to them please don't write your email
• aljgz 2y ago
  In 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 does not need too much mental processing. I have a peculiar taste in Music. I love many many different types of music, but once I find a really good piece, I'm not interested in things that are very similar to this one. Looks like if we describe musical work with high dimensional vectors, I like to find good vectors that are not too close to each other. But as the author said, Spotify keeps showing me music that's similar to what I've listened. That's exactly what I don't like (with the occasional exception of something being better than the one I've already found and replacing it). I assume I belong to a peculiar minority. The recommendation algorithms work very well for predictable majorities. Maybe someday we have an interesting "musical embeddings" model, and then people can implement personalized discovery algorithms using that?
  • zeynepevecen 2y ago
    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
    • skydhash 2y ago
      Same as GP. It takes times. Unless it’s party mode, I only listen to albums. To find new music, it takes time mostly. I decide to listen to a new genre and I seek a playlist or a compilation curated by someone. If I find someone I like, I check their albums. I also checkout the recommendations on bandcamp (people vote with their wallet there). Then there are forums and polls, and I may decide to try something out of the blue. The more you curate, the more you define your own taste. It’s then easier to describe what you like in a music and triage.
    • jcelerier 2y ago
      last.fm & the likes, friends recommendations, asking every guest to put songs in the playlist if I have a party at home
• mushufasa 2y ago
  No 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.
  • zeynepevecen 2y ago
    I’m checking that right now, thank you!!
  • Sebb767 2y ago
    If entirely new things is what you're looking for, you're not really looking for a recommendation algorithm [1]. What these algorithms try to achieve is finding unknown songs that are in the same genre to what people already like. [1] Technically "random song not in listen history" would work out, if you'd really like to call that a recommendation algorithm.
    • zeynepevecen 2y ago
      But I also don't want a totally random song eighter. I want something that vibes with me but not directly recommended through my listening history, because then they are extremely similar and feels like they're feeding me the same melodies over and over. Thats why I tried to give the "vibes" in a different format; image, rather than my listening history.
  • 2big2fail_47 2y ago
    Love NTS. Human-curated radio is still the best way to find new music :)
  • Barneyhill 2y ago
    I agree. Here’s a discovery tool I made to traverse NTS tracklists linked by common tracks ;) https://www.barneyhill.com/pages/nts-tracklists/ https://www.barneyhill.com/pages/nts-tracklists/
  • 2y ago
• ratiolat 2y ago
  Interesting. For example how would one find a "new" Tool or Deftones? Current algorithms probably don't "pick up" not-yet-so-popular things. For example Shelton San (I found out about them via word-of-mouth), although I'm frequent user of Spotify. This means that classical promotion channels are still necessary, as otherwise things get lost in noise.
  • fantasybuilder 2y ago
    I noticed that Spotify surfaces similar artists who are also of a similar popularity. So it's not like it doesn't understand that particular style, it just has to somehow pick a couple of dozen artists to show in that very coveted spot. So what worked for me in the past is finding less popular artists and then checking their similar artists.
• kundi 2y ago
  We’re building something similar with Formaviva.com on an independent music library. Please get in touch
• zippergz 2y ago
  The most interesting thing in this, to me, is just how differently people perceive and enjoy music. I find that the algorithms work pretty well for me. But novelty in melody or rhythm are not something I care about (I literally can not remember an instance of even thinking about how a melody in a new song might go, let alone predicting it). The kind of “newness” that the algorithms provide work exactly right for how I enjoy music. But it makes a ton of sense that if you are more driven by finding new melodies, they would not work well for you.
• ZoomZoomZoom 2y ago
  Even though the idea of recommendations is anything but new, literally nothing and nowhere works as expected. The only thing that comes close is based on the concept of neighbours, as implemented at Last.fm or RateYourMusic. I don't understand why is it so hard to offer something along these lines: 1. Define dominant user preferences by clustering and segmenting the field of listened genres. 2. Build a list of relevant "neighbours": 2.1 Manually added users/friends 2.2 For each of the dominant genre preferences, find users with a high level of artist intersection within that genre and add them 3. Now, for a "find similar" query: 3.1 Define a reasonable time window 3.2 For each neighbour, find points in time when they listened to the queried track/artist 3.3 Build a list of tracks/artist from the defined window around the points found 3.4 Filter tracks/artists that are too "distant" on the general genre/tag map, or lie outside of the user's dominant preferences (with a degree of boundary feathering, perhaps) 3.5 Filter if similar to negative part of the query 3.6 If novelty is required: filter artists/tracks according to the degree of their presence in the user's history
  • resource_waste 2y ago
    I think the financial incentives to promote specific artists (or songs with ads in them "GUCCI!") become the focus pretty quickly. The cost to play a song is expensive, so if you can actually profit by putting a new artist instead of paying, why wouldn't you? Sure your customer gets 3 minutes of potential garbage, but they don't realize that they generated revenue for the company just by sitting through that song. If you give your customers a great experience, they are going to listen to more music, which is bad for the bottom line. There doesnt seem to be any competition due to IP laws, so there is no incentive to be good.
  • chillingeffect 2y ago
    Confounding factors are 1. The curse of dimensionality when computong distance functions and 2. The cost function of a bad song. People get mad if they get too many things they don't like. Notice Pandora immediately sends you back to the band that seeded a station upon any thunbs down.
• rickdeckard 2y ago
  "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." I really don't think that's the main method of Apple Music or Spotify to create a list of suggestions. From what I know, (beside of dark marketing-patterns) the suggestions are created by checking what other songs people like/listen to who ALSO like/listen to this current song (or other songs you played), and the common neighbors of those songs in other playlists. (If you play music for your toddler, your future suggestions will include children's music not because it sounds similar but because "a critical mass of other people who listened to Baby Shark on repeat also listened to: Old Town Road") It is weird and it’s ironic that they call that “discovery”, as it feels more like variations of what I'm already listening to. This indicates that the persona that this platform created for you is quite homogenous and probably matches closely with many other personas on the platform, so many people who listen to the same music as you do apparently listen to _nothing else_ than this kind of music... (not trying to defend those suggestion algorithms, just analyzing the comment)
  • nihzm 2y ago
    > This indicates that the persona that this platform created for you is quite homogenous and probably matches closely with many other personas on the platform To add to this analysis, I think there may also be a feedback component to this problem that exacerbates the issue, since most users are passively using the suggestion algorithm. In other words, if the suggestion algorithm tends to create a homogenized persona of the user's taste, say, because they don't bother to actively correct it, then this persona is embedded into a cluster of people with similar personas. And because the persona is now closer to said cluster, the suggestions will become even more homogenized. Moreover, since the cluster is mostly composed of passive users, the cluster itself will tend shrink (eg in variance) and to get more homogeneous. I suspect that most algorithms do not do enough to prevent this global trapping effect, and so even if they have some method to sample "something new" for the user this becomes less and less efficient as more users rely on the algorithm for their suggestions.
  • nickburns 2y ago
    I actually do find this observation to be quite accurate for many of my own 'suggestions.' I'm regularly recommended 'new' and 'old' music that was clearly matched to my 'tastes' only by melody or, more noticeably, sample. It very much seems like if a song fits into a genre I listen to frequently or have been listening to lately, and it samples another song I've listened to before—cheap recommendation. And the greater the frequency of individual plays (i.e. the more times I've replayed any one song), the more likely that derivatives will be recommended to me. It's easy to see how this would've been baked into a human-made algorithm when you consider waveforms. Speaking only to Spotify's algorithm here. And it doesn't really bother me for obvious reasons. But it is creating something of a musical echo chamber for me.
• cainxinth 2y ago
  I’ve used everything, new and old media: Spotify, Napster, CMJ, pitchfork, bandcamp, allmusic, mojo, SoundCloud, beatport, last.fm, Apple Music… Nothing beats that one friend who used to DJ and still obsessively digs crates.
  • loudmax 2y ago
    That is a fairly close approximation to Radio Paradise: https://radioparadise.com/home https://radioparadise.com/home Radio Paradise is very much a rock station at heart, so necessarily for everyone's liking. If you're into classic rock mixed with contemporary rock, mixed with a bit of everything else, it's worth a shot.
  • toofy 2y ago
    i’ll echo this. that dj friend or like i said in a different comment, your local record store employees. college radio stations. and just other people. it really is that simple.
    • creeble 2y ago
      Especially, college radio and other free-form community radio stations. People who feel they have a calling to be a DJ sometimes actually do. I have a reasonable list of TuneIn stations (mostly US) that provide my favorite “discovery”.
  • fantasybuilder 2y ago
    In my experience literally anything beats that one friend who is a DJ. My friends - professional DJs in Berlin - haven't even heard of Can, to my absolute shock.
    • ska 2y ago
      The “and still obsessively digs crates” was important I think. DJ’ are not even close to fungible (hell, I’ve even met a couple who don’t like music much) All music recommendation engines at this time still aspire to be mediocre, they aren’t even playing the S.A.,e game as a human who is good at it. Unfortunately, such humans are unevenly distributed.
• linuxftw 2y ago
  I don't listen to any auto-play streaming service. It always devolves into the latest pop music that I don't care for. If you like old-school metal, here's some great youtube channels (no affiliation to myself): https://www.youtube.com/channel/UCCGbKiCJjph8Grazqmo7z4w https://www.youtube.com/channel/UCCGbKiCJjph8Grazqmo7z4w https://www.youtube.com/channel/UCD5Ny_jQ8cs9JXVPWXg9iNw https://www.youtube.com/channel/UCD5Ny_jQ8cs9JXVPWXg9iNw Support these small bands.
• nutshell89 2y ago
  I really wish Spotify or Apple offered the ability for the listener to simply listen all of the songs released on their platform on a day or a week, good or bad, and directly pay the artists for the songs listeners enjoy. Spotify's "New Releases" for example, tracks only music that major labels promote, or that fit a predetermined genre, or are similar to the songs and artists that you already listen to. There are smaller services yes, which allow for independent promotion and distribution (Last.fm, RateYourMusic) but these have fairly obvious flaws in how the listener can approach new music (RYM pushes ratings first and foremost, and both last.fm and rym push trending artists to their users). Instead, because the value of music is zero (really, negative since the number of listens, streams, album purchases, etc can fail to recuperate the cost to make it ), the act of distributing music presents economic risk unless the release itself can be controlled by the investors through advertisement or paid promotion.
  • fantasybuilder 2y ago
    IIRC Spotify has around 100K new tracks added daily.
• tpurves 2y ago
  The real big lie is the idea that the recommendation algos were ever actually for the user. The premise that many folks miss here is the idea that Spotify is, at best, thinly interested in recommending music that is good for YOUR interests. Spotify is the music business, and specifically the pop music business, has long discovered that's it's much more economically expedient to force feed musical taste onto the public than it is to chase the whims of organic hit-making. Payola is as old as recorded music. Spotify recommends what Spotify wants it's users to listen to. They have all kinds of side deals and marketing deals with labels, they have cheaper costs/royalties on some tracks than others. Popular tracks cached in their CDNs are probably cheaper to recommend than long tail ones etc. They have strategic priorities like gaining on apple for podcasts, and therefore injecting allsorts of podcast recos in the UI wether you asked for that or not.
• stemlord 2y ago
  I figure the problem is access. You either have the obscure music people want to discover in your db or you don't. The music available on spotify is a drop in the ocean so it doesn't really matter how searches work because a majority of the possible results simply aren't known by the platform
• assbuttbuttass 2y ago
  Spotify's recommendation algorithm sucks, but I have a lot of my favorite songs that I discovered through YouTube music's algorithm
• Mountain_Skies 2y ago
  Think they also direct listeners to cheaper to license sound-alike version of songs, especially from previous decades. I've pretty much given up on the recommendations from any of these companies. Pandora used to be reasonably good but they started playing the Studio 54 game where there was always another higher level of subscription to buy to avoid annoyances they would create. The best recommendation engine I've used was last.fm for the xbox. I could leave that on all day and rarely need to do a skip. But that was discontinued long ago, maybe ten or fifteen years ago? Haven't seen anything come close since. Amazon keeps giving me free Amazon Music but it's not even worth the bother of loading up as the system is so focused on anything and everything except my musical tastes.
• corytheboyd 2y ago
  Personally all I want out of a subscription based music service is excellent quality, constantly updated/created, thematically consistent, human curated playlists. I don’t really care if it’s super popular or fringe stuff, but I do want it to be as “good” as the other stuff on the playlist, and I want a human who also cares about the music to be making that decision. Sometimes the playlists in Apple Music scratch this itch, but it would be amazing if they were constantly updated.
  • AdmiralAsshat 2y ago
    I've got a Tidal subscription, and I've played with creating a few of my own playlists for the explicit purpose of sharing with others (as opposed to personal use). They're nothing special, but I at least try to put in some research while constructing them to bound them at a narrow time-frame/genre for accurate historical purposes. I have no idea if anyone is listening to them, though, because there doesn't seem to be any feedback system for the community playlists. That would be a useful addition, IMO. If TIDAL doesn't want to pay dedicated staff to curate playlists, they could at least make some way for the member-created playlists to get featured or gain reputation.
  • bocytron 2y ago
    Deezer has human curated playlists updated frequently, which has been my main way of discovering new artists these days. For example, the prog metal playlist as been updated 5 days ago. [0] There are lots of those playlists.. [0] https://www.deezer.com/fr/playlist/1588605745 https://www.deezer.com/fr/playlist/1588605745
    • corytheboyd 2y ago
      Hell yeah Deezer is already so much better, I’ll switch to this permanently I think. I knew it was a thing but just never thought to try it.
• iamacyborg 2y ago
  I don’t know if it’s the case anymore but I used to use last.fm’s radio service 8 or so years ago and it was absolutely great at finding and recommending me genuinely new stuff.
• quxbar 2y ago
  > 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 letting me broaden my horizons or jump down a rabbit hole from a random starting point, like a song I hear in a public space or commercial or something sent by a friend. Maybe the OP should keep their ears open to more sources of randomness from the outside world?
  • InitialLastName 2y ago
    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?
    • gs17 2y ago
      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.
      • InitialLastName 2y ago
        Not even Release Radar, but the "New Releases for You" list should probably have new releases by the artists I follow (as a basic minimum).
        • gs17 2y ago
          Huh, I don't even have that section on my Spotify. I have a "New music you need to hear this week" at the very bottom (none of it is anything I need to hear this week), but it's just generic "new music in X genre" playlists.
• Capricorn2481 2y ago
  On Reddit, there was a few threads where people were reporting that, no matter what song radio they listened to, they were getting Sabrina carpenter. Didn't matter if it was Rap, Sad Indie, Vaporwave; She would eventually come on. It's noted that her current tour is sponsored by Spotify.
• calimoro78 2y ago
  Pandora, Pandora, Pandora. No other service for me worked to reveal new songs and artists I did not know about that nailed my taste. But Pandora relies on manual tagging by music experts. Fantastic, but probably not very scalable.
  • creeble 2y ago
    Indeed. The Music Genome Project never got beyond ~250k songs IIRC.
  • underlipton 2y ago
    Grooveshark. Pandora was miss-or-ding-the-side-of for me. Grooveshark always seemed to grab me songs that I NEVER would have discovered on my own, but that resonated with me somehow. It was also a lot easier to find particular versions of songs, or indie music (particularly before Soundcloud became popular). The benefits of not having to kowtow to music industry IP BS (until it was destroyed by it).
  • hoorayimhelping 2y ago
    last.fm found me some of my favorite bands of the last 15 years.
  • bena 2y ago
    I was about to say that I've been pretty ok with Pandora so far. My wife thinks I "use it weird" as I mainly listen to the Shuffle station and have mostly various artists in my collection. Whereas she has styles and categories. And that's mostly because I don't want to listen to "Mid-90's Grunge", I want Soundgarden, Pearl Jam, etc. However, even in the various artist stations, they do play artists "similar to" as well. Which is how I started listening to stuff like Murder By Death, Eilen Jewell, Bakar, Black Pumas, and others.
  • nox101 2y ago
    A problem I had with pandora is I'd say I don't like track X so it would play other mixes of track X.
  • pragmatick 2y ago
• deleted 2y ago
  [deleted]
• cush 2y ago
  So I've been using Tidal for 5 years now, and feel they run circles around Spotify in terms of curation. Their algorithms and curated tracks are better, and they steer away from the social/gamification features and lean in to artist-centric features. For example, they've had a "credits" feature since day one - you can look up the producer, guitarist, oboeist, etc of any song, and see what other work they've done. In terms of discovering new music, there is absolutely no comparison to being able to look up the actual human behind the track. I've discovered hundreds of bands this way.
  • fantasybuilder 2y ago
    Spotify has song credits too, just FYI. In my experience, and the reason I left Tidal several years ago, is that they lean heavily into modern hip-hop, compromising relevancy for the sake of promoting "friends of the company" (Jay-Z, Beyonce, etc).
    • cush 2y ago
      Spotify only lets you read a very reduced version of the credits of a song, and you can't click on the artist to see all of their work. On Tidal, the credits are much more extensive, and you can go deep down the rabbit hole of a producers work in one click. More importantly though, Spotify doesn't directly link artists to bands they're in. For example, on Spotify, Billie Joe Armstrong is credited with his work on Green Day, but if you go to the Billie Joe Armstrong page, he isn't. On Tidal, each artist can also be broken down by their role on a project. For example, you can see just the songs that Paul McCartney wrote (turns out he wrote a track for Drake called Champagne Poetry in 2021... who knew). On Paul McCartney's page on Spotify he isn't even attributed to The Beatles
      • pimlottc 2y ago
        > For example, you can see just the songs that Paul McCartney wrote (turns out he wrote a track for Drake called Champagne Poetry in 2021... who knew). Unexpected writing credits like this usually indicate sampling. In this case [0], Drake sampled a song [1] that sampled another song [2] that was a cover of a Beatles song [3]. 0: https://en.wikipedia.org/wiki/Champagne_Poetry#Samples_and_credits https://en.wikipedia.org/wiki/Champagne_Poetry#Samples_and_c... 1: "Navajo" by Masego 2: "Michelle" by The Singers Unlimited’ 3: "Michelle" by The Beatles
• angry_moose 2y ago
  The 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 I tried to find recommendations from, I got Iron and Wine.
  • feoren 2y ago
    Don't forget the "featured artist" problem: the app is paid or otherwise incentivized to show you specific artists. Enshittification ensues.
  • munificent 2y ago
    I think a more fundamental problem is that people like music for very different reasons. Even the same person may define "similar" very differently at different points in time. If I want music "like" "Groove is in the Heart", is it because: * I want mid-tempo house-like dance music * I want major key songs with female singing * I want songs with rap interludes * I want 90s music * I want fun party music * I want music that reminds of that awesome trip I took with my friends a few years ago where we played a bunch of songs over and over There is no right answer to this question. But, outside of just looking for playlists, no music app I've seen gives you a way to specify in what way recommended music should similar to the current song. I see this effect most acutely when I listen to something that happens to be popular. For many people "heard it a lot when doing this fun social thing" is one of the main reasons they like a particular song. This was true for me too when I was younger. But for me today, I'm mostly oblivious to popularity. I just like stuff that sounds a certain way. Whenever I stumble onto a song that has a particular sound I like that happens to be well-known, the recommendation algorithm just starts throwing other popular stuff at me that sounds totally different.
    • lowbloodsugar 2y ago
      See, "Groove is in the Heart" makes me think of "Calling all units to broccolino" by Calibro 35. So I might add: * Musicians having fun with instruments.
• astrobe_ 2y ago
  "You need to enable JavaScript to run this app." What do you mean, "app"? There's no "app" there. If anyone constructed a PDF, which was itself blank but, via embedded JavaScript, loaded parts of itself from a remote server, people would rightly balk and wonder what on earth the creator of this PDF was thinking — yet this is precisely the design of many “websites” [1] [1] https://www.devever.net/%7Ehl/xhtml2 https://www.devever.net/%7Ehl/xhtml2
  • zeynepevecen 2y ago
    There is an app you are just seeing the landing page
    • astrobe_ 2y ago
      Oh, my bad! It's a "landing page"! Totally normal that it needs to 200 Kb of JS to display 1 Kb of text!
      • zeynepevecen 2y ago
        There’s an email subscription field thats why i need js hahah you’re so fond of yourself
        • msla 2y ago
          So you can't write a simple form without JS? Weirdo.
        • msla 2y ago
          What in the world are you talking about?
        • astrobe_ 2y ago
          Don't take it personally though, JS abuse is unfortunately common; just need to vent for once. But like the author of article I linked, people tend to just skip those blank pages. It's a tiny minority which is probably not the target audience anyway. Actual hackers would look at how you did it and make their own version.
• spcebar 2y ago
  I've found YouTube Music's recommendations very good. I somewhat routinely do 14 hour drives and I always end up hearing three or four new songs I love. As I've listened to various songs it's done a great job of figuring out what within the genre I'm listening to I enjoy and don't enjoy. The idea of knowing the next melody, as the author says, doesn't really bother me if I like the track, though my taste isn't very diverse.
• AlbertCory 2y ago
  I'd be quite happy if Spotify just went away. The world of music would be much better off. My solution (doesn't work for everyone): I have a large library on the microSD card on my phone, and set the music player to Shuffle. Quite often a song comes on and I think, "Wow, I own THAT??" OK, I'll admit that doesn't play any new music. However, no bills for bandwidth!
  • MetaWhirledPeas 2y ago
    > I'd be quite happy if Spotify just went away. The world of music would be much better off. Why? It's almost exactly the same experience you get from all the competing services, and that experience is fantastic: any album, any song, instantly ready to play. > I have a large library on the microSD card on my phone, and set the music player to Shuffle. This is a fine situation to be in but from the perspective of your fellow music consumers it is highly undesirable. Music libraries involve a lot of time and money. For the cost of one album per month you can subscribe to an unlimited service. > no bills for bandwidth! This definitely sounds unique to your geographical situation. I admit that streaming services are bad for artists who want to make money from album sales, but asking consumers to use something else would be like asking people to ride horses to work in order to keep farriers in business. The 1990s are long gone; being a famous musician isn't guaranteed to make you rich anymore. Meanwhile the not-famous musicians who make up 99.999% of the music population can happily continue not making any money off of album sales the same way they've always done.
    • AlbertCory 2y ago
      > happily continue not making any money You got that right. This is a totally vapid, progress-is-great response. Do you work for Spotify? Read some Ted Gioia and get cured of that.
• lowbloodsugar 2y ago
  When I have people over, I hand them the iPad that runs the audio system (I use Roon, Qobuz and Tidal but I imagine anything will work). When they play new and interesting things, they are now in my history. My favorite discovery from this was Massive Attack's Teardrop, which was a track I had heard before (and loved) yet completely forgotten about years later.
• JohnMakin 2y ago
  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.
• MrDrMcCoy 2y ago
  Way 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.
  • galdosdi 2y ago
    There was an article in the Times recently about how Spotify is no longer solely using "how much do we predict the user will like this song" as a metric, but now is also considering "how much do we pay this artist per play" to optimize for cheaper higher-profit-for-spotify music.
  • terribleperson 2y ago
    I used Pandora a lot when I was a teenager, and experimented a bit. If you were listening the same time I was, the size of the library probably wasn't the primary issue. Presumably their recommendation algorithm and the Music Genome Project tagging allowed them to, given a set of tags, find similarly tagged songs. This worked really well. It's how they used it and how they picked what track to play next that caused issues. First, thumbs up. As far as I could tell, at the time Pandora would strongly prefer to play a track you'd thumbsed up on a station over anything else, as long as it was available to play, which mainly just required it to not have played to you in the last two hours. So if you used thumbs up the normal way, a well-used station would eventually turn into a loop of things you'd already heard. Second, the way they used the algorithm - it seemed to me like they only or mostly used the station seeds as the input, there was no blending going on, and if thumbs ups impacted it, well, they had their own problems. That is, if you had a station with two seeds, it played some songs close to one seed, then it switched to the other seed and played some songs close to the other seed. Skipping would usually bump you to a different seed. To get around all this and get a variety of new material, I created a station with a lot of seeds - 25 to 50 or more - and never thumbsed up anything on it.
• mountain_peak 2y ago
  Here'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).
• fallinditch 2y ago
  Another good music discovery method is to use AOTY - albumoftheyear.org I find their comprehensive section of Lists (featuring lists from all the major publications) and aggregate lists is inspiring for discovery. For example, check out this list of the best albums so far this year according to The Quietus, containing some great stuff your algorithm would never consider: https://www.albumoftheyear.org/list/2284-the-quietus-albums-of-the-year-so-far-2024/ https://www.albumoftheyear.org/list/2284-the-quietus-albums-...
• nox101 2y ago
  The service I got the most use out of was Rhapsody back in like 2005. Instead of playlists and "radio" it listened artists that influenced this band and artists that were influenced by this band. That lead directly to music I liked. Otherwise, most of the services (Spotify, Apple Music, Youtube Music) have been really bad at recommending music. No amount of downvotes on songs seems to give their algos any input on bands I don't want to hear. Further, they always seem to devolve in to ridiculous recommendations. I've asked for "Louis Prima" radio and have them insert hip-hop or rap. Google Play Music did better than those 3 but that died.
• TheCleric 2y ago
  Pandora has always been the best at this (for me at least). Especially because they are the only tool I know of that has a MUST HAVE feature for me: contextual thumbs up/down. If I'm in the mood for a certain mood/genre, that's what I want to listen to. Even if a song comes on that I normally love, if it doesn't fit the mood, I want a way to say "that doesn't belong here right now". So in Pandora I start a station and can thumb down songs that don't fit that station's theme, and Pandora understands that doesn't mean I don't like that song. It just means I don't like that song in this context. As far as I've seen, every other service only registers these globally. Either I like a song or I don't. That doesn't make any sense to me.
• scelerat 2y ago
  It's not the only way to discover new music, but in the age of 99.9% online presence, I feel simply going out to listen to music is way overlooked. Most cities and metro areas with more than a few hundred thousand people have jazz, punk, indie, hip hop, country, choral, and classical scenes. Certainly true of any ville with a university. Check out a local weekly, listen to college radio, look at the online calendars of local venues and clubs, take a risk, check something out you've never heard of before. You may be surprised. There are musicians and scenes which fly under the radar of widespread Spotify and Youtube popularity which nevertheless deliver great performances and often themselves lead to other new, interesting discoveries. A side effect is you may also end up talking to someone at these gathering places and making new acquaintances: again, another great way to discover music and other things. There is so much that has been built online whose subtle or sometimes overt goal seems to be to eliminate actual human contact. I suppose that is attractive for some, but I feel the opposite is what a lot of people yearn for, and it can be achieved with just a little bit of investment.
  • ragazzina 2y ago
    > Most cities and metro areas with more than a few hundred thousand people Maybe in Asia it's different, but in Europe and in the USA only 10% of the people live in a city with more than 300k inhabitants.
• frankus 2y ago
  I think I speak for most people when I say I want my music "discovery" playlist to be something like "mostly stuff that sounds like stuff I've indicated that I like" with a small amount of "not sure I'll like it, but suprise me". It sounds like OP is looking for the ability to turn up the "surprise me" factor at the expense of maybe having to skip a few more songs that just aren't clicking with them. So maybe something like a "temperature" knob is in order?
  • joe_the_user 2y ago
    You're welcome to your preferences but I think you need evidence to claim you "speak for most people".
    • deleted 2y ago
      [deleted]
    • boldlybold 2y ago
      I think it's an accurate statement. I've heard similar sentiment from friends in the car with spotify on.
  • JeremyNT 2y ago
    YouTube music actually has the ability to set how this works with its "radio" feature. You can set the seed artists, then select levels for "artist variety" and "music discovery." You can also filter based on tags.
• ezpuzzle 2y ago
  you could suggest music from artists that have released music on the same record label within +/-5 years of what you listened to and get close enough. the human curation is already "baked in". graph traversal playlists are the most interesting idea to me, especially if you can put some bounds on (i.e. weight positively and negatively certain artists in the graph)
• TaurenHunter 2y ago
  I kinda like what they did in https://maroofy.com/ https://maroofy.com/ in that it lists songs very close to what I specify. However I would prefer a service that allowed me to tell what I don't like and then use that preference to filter out everything similar to it.
• Triphibian 2y ago
  One of the things I find frustrating about music suggestions is that the app/algorithm doesn't care why you like a certain band. A long time ago I asked Pandora to make David Bowie station and it rolled me a generic classic rock station -- Zeppelin and the Stones. I was hoping for old school glam, maybe T-Rex and Eno. There's no way to communicate that desire to our music players. To say, "please don't think me a basic AF music listener." I have noticed an interesting phenomenon around TOOL. If you start a playlist on Apple Music from TOOL it will start playing everything from Metallica to Nirvana. A lot of people like TOOL for a million different reasons and Apple doesn't know any different except for the overlaps in taste. If you play a Mike Patton band, such as Mr. Bungle though -- you will get some TOOL in your playlist -- because both bands are esoteric and often challenging. I'm looking forward to the day (or wishing maybe) when my app considers these factors. For me the issue isn't discovery, but rather I want my robot DJ to vibe more closely with me.
  • Terr_ 2y ago
    It seems some of these services (e.g. Spotify) don't really do musical similarity, but instead emphasize indirect "other fans also like" similarity. That tends to disregard many reasons you like a particular track, and does especially badly when the liked-track isn't part of a uniform style for an album or artist. I recognize it's a heck of a lot easier to implement, but it's still a disappointment.
    • dropofwill 2y ago
      They definitely do both, in the public recommendations API you can see vestiges of the old EchoNest acoustic properties along with some new ones they’ve come up with. It’s fun to play around with. https://developer.spotify.com/documentation/web-api/reference/get-recommendations https://developer.spotify.com/documentation/web-api/referenc... The guy behind Every Noise at Once (engineer at EchoNest/Spotify until the recent layoffs), has some interesting thoughts about this topic: https://www.furia.com/page.cgi?type=log&id=478 https://www.furia.com/page.cgi?type=log&id=478 He’s quite biased towards not using ML or acoustic characteristics for recommendations. But even if you disagree it is interesting to hear about how things were working under the curtain (for daylist in this case).
• frakt0x90 2y ago
  There's a VST that creates embeddings of all the sound samples you have in a directory and then projects it down to 2d so you can visually explore and find sounds you're looking for. Similar sounds are near each other. I always thought doing that with the entire spotify library would be amazing. Give me a low dimensional space to explore the library. Even cooler if the embeddings have similar geometric properties of language embeddings where I could do arithmetic with songs to find interesting combinations.
  • cmgriffing 2y ago
    That sounds awesome. Link please?
• deepsun 2y ago
  Google Music used to have a good algorithm: * There was a thing called "Library" in addition to "Likes". Basically all "your" songs, not necessarily liked you. * When clicking on a "Feeling Lucky" button, it selected a random song from Library, and started an auto-generated Radio off it. It allowed to listen to random songs based on your library. I miss that in Spotify.
• clueless 2y ago
  For the electronic music sub-genre, some streaming compnay needs to buy https://www.1001tracklists.com/ https://www.1001tracklists.com/ for their playlist data (i.e. DJ set lists from soundcloud) and incorporate it into their recommendations. Your welcome Spotify!
• wisaacj 2y ago
  I love it. A kind of musical search engine for synaesthetes
• gwerbret 2y ago
  Music discovery -- or discovery of movies, TV shows, love interests, or anything else that caters to human preferences -- is an enormously challenging problem that those whose business it supposedly is to solve have largely given up on. Part of the problem is exemplified in this thread: there are endless different ideas of what the ideal $ITEM discovery algorithm should do. Even if the Spotifys of the world were to deploy some modern AI-based tools to fix the problem, the level of tweaking each listener/watcher would need would be so extensive as to belie the entire effort. So they don't, for at least 2 reasons: First, it's hard, as we all know. Second, it turns out that the "best $ITEM discovery algorithm" accolade doesn't pull in that much extra revenue. It's far better (for them) to use people's expectations of such an algorithm to profit from a bait-and-switch. As an example, see Amazon's search engine.
• Yodel0914 2y ago
  Like many people here, I've never found algorithmic recommendations useful. What works best is what has always worked best: recommendations from people with similar taste. Back in the day, this was friends lending me CDs. Now, I follow a bunch of people on Mastodon who almost only post about music. I've also found following the releases from specific smaller record labels quite useful - often the artists on a label will fit a certain vibe, even if they don't specifically overlap in genre.
• navaed01 2y ago
  Really interesting idea, using images to generate playlists. I’m curious what interpretation is being done on the image. I find myself in the spotify ‘discovery’ trap getting slowly funneled into a steady universe based on likes from previous weeks’ playlist, where everything is new but also the same. I’ve often correlated music with mood and color and it can be easier to express what you are seeking with colors vs. expressed genre, which is just a broad classification
• rldjbpin 2y ago
  the underlying assumption for these systems for most people seems to be that all songs are treated equally. this is clearly no longer the case for any major streaming platform. their own logic to promote might be too egregious now. same seems like for shuffling through a large playlist. one can try to empathize to the ones designing this (e.g. shuffle anticipating network drops and switch to cached results for the next track) but self-discovery will remain evergreen.
• micheljansen 2y ago
  I don't have evidence for this, but my working theory is that there is too much money to be made in promoting certain artists / songs for music recommender systems to remain objective. If supermarkets auction off premium shelf space to the highest bidder, what's stopping Spotify, Tidal, Apple etc. from doing the same? Want to create a new pop star? Hand over the cash and we'll put it in millions of people's "Discover" playlist.
  • herbst 2y ago
    These popular playlists are often already owned by the music corps. And I am sure there is a price tag for those that Spotify manages. Next to that there is also the shadow fact that there are millions of dollars and more in fake plays, subscribers , ... SMM panels are getting big because the music industry doesn't allow for anything less than instant fame.