[HN Gopher] The lie of music discovery algorithms
___________________________________________________________________
The lie of music discovery algorithms
Author : zeynepevecen
Score : 118 points
Date : 2024-07-30 09:18 UTC (13 hours ago)
(HTM) web link (www.zeynepevecen.dev)
(TXT) w3m dump (www.zeynepevecen.dev)
| jerrygoyal wrote:
| how does it technically work?
| counterpartyrsk wrote:
| Looks like OP is harvesting emails more than sharing their
| (completed) work based on this and their other project
| https://www.zeynepevecen.dev/
| zeynepevecen wrote:
| Nope my website is way out of date, sorry :) will remove that
| section entirely
| zeynepevecen wrote:
| 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 wrote:
| 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.
| zeynepevecen wrote:
| Thanks, that was something I was already considering. Do
| you know where can I find models specialized in this area?
| Because it is kinda niche, I couldn't find something that
| maps images into playlists directly, thats why i went for
| llms
| BillFranklin wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| It works pretty well for me. Do you use the like and dislike
| buttons, subscribe to channels you like, etc?
| Retric wrote:
| > subscribe to channels you like
|
| That makes things worse IMO. My favorite videos tend to be
| one-offs not channels producing regular content.
| Unsubscribing from everything definitely improved my feed.
| im3w1l wrote:
| How would you distinguish one from the other given the data
| youtube has?
| Retric wrote:
| The algorithm is limited by their choices not the current
| system as they can update the UI.
| Mountain_Skies wrote:
| YouTube didn't help things any when they neutered the dislike
| button. It's still there but functionally useless. Yes, we
| all know why they did it to save the feelings of a few
| political staffers at campaigns aligned with the values of
| workers at Google but it's been an absolute godsend for
| scammers and terrible for signaling interests to the
| recommendation engine.
| layer8 wrote:
| 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.
| AmericanChopper wrote:
| I think spotify's playlists are quite decent. I think they used
| to be a lot better than they are now, but I suspect that most
| recommendation systems decay over time. I suspect they don't
| handle the recommendation feedback very well, so they can start
| off introducing people to new things, but then become a bit
| more static and just reinforce the same habits over and over.
|
| I think YouTube's recommendations used to be excellent,
| especially for music, but I've personally found it to be
| terrible recently. It no longer recommends anything new to me,
| and I suspect that it's way over-tuned. If I see a video that
| looks mildly interesting I'm a bit hesitant to watch it,
| because I don't want YT to decide that it should become 50% of
| my feed for the next week. Which from the recommendation
| system's perspective is just weakening the signal I'm feeding
| to it even further.
| techaudible83 wrote:
| This is an interesting point and I wonder if part of the
| issue is that a mature, extremely popular algorithm trends
| towards the lowest common denominator. I don't mean this as a
| judgement of taste, it just seems to me that people engage
| with art in different ways. Maybe the spotify algorithm is
| perfectly tuned to the majority of people who just want to be
| able to find more songs that fit the kind of sound they like
| or find something to throw on in the background. But for a
| significant minority of others like myself and OP, it's just
| not tuned to what we actually want from new music.
|
| I also feel the same as you regarding the youtube algorithm.
| I actually get better recommendations sometimes by just
| logging out since it will try showing me new stuff.
|
| One thing I'm not sure about is whether it's actually the
| algorithm's fault or if my expectations have become
| unrealistic and made me lazy. I used to read magazines and
| blogs to find new music. There are still tons of people
| writing about their favorite music, labels that act as
| curators, etc. I just don't seek them out and instead expect
| to be spoonfed by the algorithms. Even if this is true
| though, I suspect many of these algorithms could do a better
| job.
|
| Also RIP Netflix's old recommendation system. I guess it
| wouldn't make sense when they can't license every movie like
| they used to, but I remember it being great. Although maybe
| it was just pretty good and I was younger and less familiar
| with the back catalog of good films.
|
| That's the other thing I wonder - am I just getting older and
| less excited about new things? There used to be a real
| vitality to finding something new and exciting. Now it kind
| of feels hard for anything to feel that fresh anymore, it all
| seems like variations on the same core ideas. I do still find
| new stuff that I like, but it doesn't have the same thrill.
| Maybe I'll always be chasing that dragon of youth haha.
| ErigmolCt wrote:
| Music has so much power over people!
| gnulinux wrote:
| 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.
| DrinkWater wrote:
| 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 wrote:
| 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
| bsenftner wrote:
| 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 wrote:
| 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 wrote:
| I've been wondering how well a word2vec on song lyrics would
| work; just completely ignore the music and pair up subject
| matters.
| galangalalgol wrote:
| 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 wrote:
| 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.
| bsenftner wrote:
| A perfect example of lyric dominant music, which I own a hug
| amount, and feeds right into hip hop and then Johnny Cash and
| The Clash.
| a-french-anon wrote:
| > with the lyrics, with the intellectual content of the music
| and not just the dressing.
|
| > Marvin Gaye, Public Enemy, Rage Against The Machine, Beyonce
|
| Thanks for the laugh, man, I needed it.
| DiggyJohnson wrote:
| Even though you'r being mean I feel the need to defend you,
| only because I agree that this was one of the most
| unrelatable things I've ever read on the site (i.e. GP's
| preference for music with a political or social theme in the
| lyrics rather than a specific genre, theme, sound, style, or
| mood).
| esafak wrote:
| I'm pretty certain Spotify uses lyric embeddings as an input to
| the recommender. They'd have a hard time recommending podcasts
| otherwise.
| zeynepevecen wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| last.fm & the likes, friends recommendations, asking every
| guest to put songs in the playlist if I have a party at home
| toofy wrote:
| 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 into and going on rants about music
| which is outside of mainstream fluff. it's like this with any
| $subject involving wonks. we're insufferable to anyone who
| isn't into our particular genre of technology. food wonks are
| insufferable, car geeks are insufferable, gamers are
| insufferable. that's ok, if you're looking for someone who is
| a geek in a topic, you're likely to become one too :p just be
| normal around $subject non-wonks and you'll be fine.
|
| but yeah, music nerds working in a good record store really
| do know their stuff.
|
| other places:
|
| - music nerd streams on twitch
|
| - music reviewer youtube channels
|
| - college radio stations (most have an online presence) 770
| radiok out of minneapolis is incredible
|
| - kexp out of seattle is absolutely amazing (they're heavily
| online as well.)
|
| - just about every mid+ sized city has some amazing radio,
| usually found in the low FM areas.
|
| at the end of the day though, it's other people. there are
| far too many variables for every _individual_ which drives
| why they may or may not like a song at any given moment.
| other humans are still absolutely unmatched when it comes to
| navigating this.
| gs17 wrote:
| > 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.
| Semaphor wrote:
| This probably won't work for most people, but as I mostly
| like metal, I simply check all metal releases that seem
| slightly to my tastes according to the subgenre. Then when
| this sampling seems at least somewhat positive, I play the
| full album after release. That usually ends in sampling songs
| from 30 albums, listening to ten albums, and buying 1-2 every
| Friday. Never had an algorithmic recommendation system that
| worked for me.
| khafra wrote:
| If you have any taste at all other than "maximally dissimilar
| to anything I have liked before," there should be a feature
| that predicts songs you would like.
|
| If your taste is exactly "maximally dissimilar to anything I
| have liked before," that's actually pretty easy to calculate
| from the embeddings as well.
| Tostino wrote:
| It didn't sound like op wanted maximally dissimilar from what
| they've liked before, but instead maximally dissimilar from
| what they've listened to recently.
| esafak wrote:
| Either way, a preference for novelty can be measured. They
| also let you edit your Taste Profile it seems:
| https://support.spotify.com/us/article/your-taste-profile/
| diob wrote:
| I'm not sure how the Spotify recommendation algorithm works at
| all, but for some reason I imagined them doing fancier things
| than looking at my liked songs and finding similar ones. I
| would've thought they'd build a profile of you, and then find
| similar user profiles and show you songs those folks liked that
| you hadn't found yet.
|
| That's gotta be how they do it, right? I'm probably wrong.
| somethingreen wrote:
| I feel those are how Pandora and Last.fm (used to?) work
| respectively. Nowadays everything seems to just put a bunch
| of tags on a track and suggest you things with the same tags
| to the tracks you liked. Doesn't even need to match the same
| combination of tags, just some number of them. The problem
| is, you probably care about the small, specific tags, and the
| system cares about wide "popular" tags. If you like a couple
| niche genre covers of songs that happen to be featured in TV
| openings/OSTs, you are not getting more songs in that genre -
| you are getting a bunch of covers and OSTs.
| entropicdrifter wrote:
| I wish I had a music recommendation service built on
| Pandora's immense dataset of music tags that could build me
| a playlist that I could link back to whichever music
| service I happen to be using at the time. I could have it
| do things like require at least 3 tags in common between
| adjacent tracks such that it could jump around between 2
| dozen genres but the transaction between any 2 given tracks
| isn't too jarring. It'd also be nice if I could tell it to
| make a playlist where every song shares one particular tag
| in common.
|
| Maybe I'll build that. Sure would be nice to have.
| fantasybuilder wrote:
| The primary advantage of Pandora's algorithm is the
| human-labelled Music Genome database. I haven't seen any
| other company do music discovery as well as Pandora, and
| don't expect that to change any time soon.
| entropicdrifter wrote:
| Right? I feel like it might be worth licensing access to
| the Music Genome db and building a small business off of
| that
| ssalazar wrote:
| I have no specific insider knowledge, but a decade+ ago they
| bought a company called the Echo Nest that was developing
| some of the best audio signal analysis algorithms around, I
| assume much of that influenced their recommender system.
|
| Nowadays, they have a quite busy research department so I
| would imagine that recommendation is quite fancy indeed:
| https://research.atspotify.com
| aworks wrote:
| Glenn McDonald, formerly of the Echo Nest and Spotify, has
| a new book that talks a lot about music recommendations.
|
| https://www.canburypress.com/products/you-have-not-yet-
| heard...
| madmountaingoat wrote:
| 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 the process is constantly being experimented
| with. Different custom playlists might be using a different
| combination of tech doing those basic steps.
| vhiremath4 wrote:
| So collaborative filtering?
| janalsncm wrote:
| 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.
| quest88 wrote:
| You do belong to a minority! Most people prefer the same music.
| All roads lead back to Katy Perry for the majority.
| gtpedrosa wrote:
| Instead of relying on things like "Playlist made for you" I
| still like leveraging the algorithm to discover "new vectors"
| by actively going to a song that some aspect caught my
| attention and going to its radio (only tried on Spotify).
| Sometimes I'm surprised with new soundscapes.
| 0xdeadbeefbabe wrote:
| You aren't the only one. The algorithm recommends overplayed
| songs that may be related but I don't ever want to hear again.
|
| Maybe these music services should ask you for music you hate,
| and start from there instead.
| emporas wrote:
| 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.
| BobaFloutist wrote:
| > 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.
|
| It's the classic problem of "Ok, but how do I sort these by
| which ones are actually any good?!"
| digging wrote:
| > I'm not interested in things that are very similar to this
| one.
|
| Are you sure this is an accurate description of your taste? Or
| do you mean "I'm not interested in things that are similar, but
| lower quality"?
|
| I'm very much a weird-music enjoyer, and I _often_ have the
| latter problem where "similar" songs actually just don't
| capture the same vibe as the truly engaging new song I just
| heard. But that's not because the algorithm is choosing music
| that's _too similar_ ; it's the opposite. It's _trying_ to
| choose something similar but can 't, so it just picks the next-
| best thing which I actually don't like.
| mushufasa wrote:
| 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 wrote:
| I'm checking that right now, thank you!!
| Sebb767 wrote:
| 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 wrote:
| 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 wrote:
| Love NTS. Human-curated radio is still the best way to find new
| music :)
| Barneyhill wrote:
| I agree. Here's a discovery tool I made to traverse NTS
| tracklists linked by common tracks ;)
|
| https://www.barneyhill.com/pages/nts-tracklists/
| fallinditch wrote:
| 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
| ratiolat wrote:
| 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 wrote:
| 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 wrote:
| We're building something similar with Formaviva.com on an
| independent music library.
|
| Please get in touch
| zippergz wrote:
| 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 wrote:
| 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 wrote:
| 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.
| rickdeckard wrote:
| "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 wrote:
| > 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 wrote:
| 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 wrote:
| 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 wrote:
| That is a fairly close approximation to Radio Paradise:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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.
| fantasybuilder wrote:
| My point is more about DJ specialization I guess. The vast
| majority of DJs I know personally still dig crates all the
| time - but they are techno/house/D&B/etc DJs, they know
| close to nothing about music outside of these genres. This
| goes so deep that some German techno DJs haven't even heard
| of Krautrock, the German scene that in many ways was a
| precursor of electronic music.
| DiggyJohnson wrote:
| Why is it weird that a DJ friend hasn't heard of a artist
| that you are a fan of?
| fantasybuilder wrote:
| German beat-oriented DJs haven't heard of one of the most
| influential German bands that had a critical impact on
| beat-oriented music? Just an odd thing for people who
| dedicated their life to music.
| linuxftw wrote:
| 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/UCD5Ny_jQ8cs9JXVPWXg9iNw
|
| Support these small bands.
| nutshell89 wrote:
| 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 wrote:
| IIRC Spotify has around 100K new tracks added daily.
| tpurves wrote:
| 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 wrote:
| 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 wrote:
| Spotify's recommendation algorithm sucks, but I have a lot of my
| favorite songs that I discovered through YouTube music's
| algorithm
| Mountain_Skies wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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
| corytheboyd wrote:
| 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 wrote:
| 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 wrote:
| > 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 wrote:
| 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 wrote:
| 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 wrote:
| 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 wrote:
| 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.
| johncalvinyoung wrote:
| This is my experience as well... I have a very broad music
| taste but with some main themes. I find Spotify's algorithm (11
| years of Premium) to regularly surface things I'll like,
| whether new music from artists I already know, music
| correlating strongly with known tastes, or every once in a
| while something that seems out of distribution but I like it
| anyway!
|
| It probably helps that the strongest areas of my taste are
| relatively small or niche genres, like Scottish trad and Celtic
| (folk) rock. In those niches, similar-but-different is often
| distinctively different in actual experience. Sure, there's
| covers of the same song from time to time, but I actually do
| like enough of those not to be bothered, if they bring
| something new.
| Capricorn2481 wrote:
| 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 wrote:
| 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 wrote:
| Indeed. The Music Genome Project never got beyond ~250k songs
| IIRC.
| underlipton wrote:
| 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 wrote:
| last.fm found me some of my favorite bands of the last 15
| years.
| bena wrote:
| 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 wrote:
| 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.
| cush wrote:
| 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 wrote:
| 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).
| drivebyhooting wrote:
| Oboeist? That is oddly specific. Why that example?
| tunesmith wrote:
| I took it as an example of a writing technique to imply the
| breadth of "credits" they support. Hope that helps.
| MattGrommes wrote:
| Some people like particular instruments. My son plays the
| bassoon and loves trying to look up who plays on a song if he
| hears one.
| 2o93u4592u wrote:
| I used Tidal twice, for a year or so each time, and I found
| that their recommendations were the best by far. But their app
| was so insanely buggy. On multiple different phones it would
| have to be force-closed and restarted about hourly. Usually it
| froze when starting a new song. The whole screen would be
| frozen and unresponsive. Now I use Apple music and the
| recommendations are garbage, and it also freezes frequently,
| but specifically only when I wake the app up from sleep.
| thinkingtoilet wrote:
| Pandora is still really good at that too. I happily pay for it.
| angry_moose wrote:
| 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 wrote:
| Don't forget the "featured artist" problem: the app is paid or
| otherwise incentivized to show you specific artists.
| Enshittification ensues.
| munificent wrote:
| 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 wrote:
| 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.
| belthesar wrote:
| Ironically, this is something that I think Pandora solved
| quite well with their recommendation engine. By virtue of
| creating a station around a particular vibe, even if 5
| playlists all started with the same seed song, weighting
| other songs up and down on each station would curate a
| different listening experience, by virtue of finding how
| those are similar. Where Pandora was limited (at least, the
| last time I used the service) was the pre-seeding process is
| a bit arduous and opaque. I'm not sure how you make that easy
| to interact with, as going a layer beneath to the "why" a
| song was recommended and allowing folks to influence the
| graph at that layer sounds like a daunting UX challenge.
| gs17 wrote:
| > 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.
| astrobe_ wrote:
| "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
| zeynepevecen wrote:
| There is an app you are just seeing the landing page
| astrobe_ wrote:
| 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 wrote:
| There's an email subscription field thats why i need js
| hahah you're so fond of yourself
| spcebar wrote:
| 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 wrote:
| 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 wrote:
| > 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.
| lowbloodsugar wrote:
| 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 wrote:
| 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 wrote:
| 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.
| musictubes wrote:
| Last.fm had the best categorizing features I ever saw. Songs
| would. It only be listed under "female artist" but would also
| have things like "extensive vamping," that really got to the
| heart of what the song was about. They got closer to
| understanding _why_ I liked songs than any other service. All
| of the other services feel rather dumb when it comes to
| preferences. It feels like they still rely on associating other
| people that liked artist x also liked artist y. As a music
| aficionado it's infuriating.
|
| Apple has tried to help by using human curated playlists but I
| frequently find myself thinking I have better taste than their
| "experts."
| galkk wrote:
| > Apple has tried to help by using human curated playlists
| but I frequently find myself thinking I have better taste
| than their "experts."
|
| It feels like all the time, when there is human curation
| factor, it ends up being sold off, gamed, exchanged for
| favors etc.
| bsder wrote:
| > Whatever happened to the good databases and their algorithms?
| They definitely used to exist.
|
| It was called a record store employee, and they no longer
| exist.
|
| _There 's_ an AI search engine I'd like to see ...
|
| Even the "market segmentation" of pop music still doesn't work
| for crap. Even something as basic as "Gee, I like 80s New Wave,
| how about recommending some artists born roughly in the 21st
| century who would fit?" seems to be totally beyond the pale of
| anything currently existing.
| MrDrMcCoy wrote:
| My tastes have always been niche enough that most record
| store employees would give me the "deer in the headlights"
| look or condescend to me when I asked for a particular artist
| or similar that I found on Last.fm.
|
| If the database quality of current Last.fm were similar to
| its state back when it had radio, I would think that an AI
| trained on their data would be pretty good. With the current
| state of it... It would have to be crap. Heck, even if an AI
| model could be trained on the play counts of every song of
| every user on every streaming service, I'm not sure it could
| approach the curated relational algorithm that Last.fm had at
| its peak. Would definitely love to see an attempt, though.
| mountain_peak wrote:
| 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 wrote:
| 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-...
| nox101 wrote:
| 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 wrote:
| 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 wrote:
| 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.
| frankus wrote:
| 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 wrote:
| You're welcome to your preferences but I think you need
| evidence to claim you "speak for most people".
| boldlybold wrote:
| I think it's an accurate statement. I've heard similar
| sentiment from friends in the car with spotify on.
| ezpuzzle wrote:
| 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 wrote:
| I kinda like what they did in 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 wrote:
| 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_ wrote:
| 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.
| MrDrMcCoy wrote:
| At its peak, Last.fm was pretty good at this. It had enough
| data on "people that like these songs also tend to like these
| songs" that it would generally know what to recommend. I miss
| those days...
| frakt0x90 wrote:
| 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 wrote:
| That sounds awesome. Link please?
| deepsun wrote:
| 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 wrote:
| For the electronic music sub-genre, some streaming compnay needs
| to buy https://www.1001tracklists.com/ for their playlist data
| (i.e. DJ set lists from soundcloud) and incorporate it into their
| recommendations. Your welcome Spotify!
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