Spotify - anyone heard of it?

Thanks. I'll see what I can find out.

Those Braxton and Davis unavailable songs are all at the label's requests, in a technical sense. I mean, Spotify didn't take any action of our own to make them unavailable. The Miles Davis ones are unavailable in the same inexplicable patterns on Apple Music, too. We will pursue with the source labels, as it's hard to believe this is an intentional request. Probably some database-field at Sony or wherever got mis-set somewhere once, and then nobody ever noticed or fixed it.

The long-track-unavailable thing seems a holdover from peak a la carte downoading, to force purchase of the entire record. Don't want to let an album of two seventeen minute tracks to go for two bucks. In a Silent Way gets fixed, but not the deeper catalog stuff.

Yeah, I bet that's literally correct, and the labels have a single no-download field in their database that they've been using for streaming, forgetting it was set for downloading.

glen, what about the local files thing? Seems pretty essential to the "Spotify-as-your-single-music-player" experience.

does anyone else not have access to the discover playlist yet? everyone's talking about it and i'm still waiting...

i only got it last weekend. btw it's utterly as good as people say it is.

I've had three weeks' worth of discover playlists. All roughly the same - good enough music that I don't skip many tracks, and the majority are new to me. But nothing so far that has compelled me to dig deeper with any artists or play certain songs over and over. And the playlist refuses to acknowledge that I listen to ambient music. It seem to only recognize that I listen to Wilco.

my first discover weekly list sounded like a string of public domain lounge electronica, but the second one was quite different. maybe the genre will move around from week to week.

discover playlists seem to have diminishing returns for me, maybe I'm just not seeding them well enough

does it depend on what you played the past week?

I don't work on anything remotely related to local-file handling, so I don't have any insight there, I'm sorry. I know people are working on it, but I don't know what the issues are.

Discover Weekly doesn't depend only on what you played in the past week, no, but it's weighted towards recent listening, so it should evolve along with your listening.

Re the lack of ambient music, mine often has no metal. But this is just the beginning.

discover weekly is designed to work off natural listening habits, rather than react to users trying to force certain results by stacking their play history, yeah? if so, just listening to what we like is probably the best way to get good recommendations.

Not sure I believe "unnatural" listening is a thing. If you think you're gaming Discover Weekly by listening differently, I call that exploration.

Besides, if you want to hear some kind of thing in particular, go to everynoise.com and look it up.

whoa that site is incredible

o wow

that's your baby, right glenn?

Well for me, a lot of my Spotify listening is spent discovering new music that I haven't heard before, often full albums or ILX playlists, rather than listening to stuff that I legitimately love, which affects my Discovery playlist. So I've tried to fix that in the past week by listening to more of my favorite songs and artists, though the fact that I'm also spending time listening to my Discovery playlists is going to reinforce the artists on those as well.

I don't work on anything remotely related to local-file handling, so I don't have any insight there, I'm sorry. I know people are working on it, but I don't know what the issues are.

Thanks. I wouldn't be surprised if they've begun to move away from the "one browser" thing given the recent focus on Discovery.

One trend I'm beginning to worry about a bit w Spotify is that artists are starting to cut side deals for "preferred" streaming services, which would ultimately lead to a bunch of services that have 97% the same thing with that last 3% spread across 5 different services, essentially ruining the all-in on demand experience for all but the most exclusive set of subscribers.

Yes, sorry, I didn't mean to be coy, everynoise.com is my thing.

whoa that site is incredible

o wow

I would like to echo these sentiments re: everynoise.com

^^^^^^

finally got a really good Discover Weekly playlist this week

discover weekly is uneven as hell, last two weeks it was like "why do u think i like any of this lol spotify, ur dumb" and then the one i got for this week is pretty damn all right thus far

It certainly seems determined to try and get me into the whiny voiced indie that I haven't listened to for 15 years. Still, about five tracks per week pique my interest, maybe not a great percentage but probably no worse than back when radio was my regular discovery channel.

is this all because it's using your playing of last week's recommended racks in figuring out this week's?

(is it a spotify home-grown thing or does it use a recommendation engine like gracenote / echonest / senzari?)

my weekly discover playlist seems better, too. i am very susceptible to the enthusiasm of others, though.

My Week 1 Discover playlist was excellent, but Weeks 2-4 have been way off the mark. However, all my partner's playlists have been bloody marvellous. He uses Spotify much less than I do, and only to listen to music that he already loves - whereas I'm forever dipping into new music speculatively, with inevitably mixed results.

ugh i still don't have discover weekly yet, thanks obama spotify

My Week 1 Discover playlist was excellent, but Weeks 2-4 have been way off the mark. However, all my partner's playlists have been bloody marvellous. He uses Spotify much less than I do, and only to listen to music that he already loves - whereas I'm forever dipping into new music speculatively, with inevitably mixed results.

― mike t-diva, Monday, August 10, 2015 2:11 PM (43 minutes ago) Bookmark Flag Post Permalink

this has been my experience -- week 1 was good, subsequent weeks were "but I already *have* opinions on banks and bat for lashes and the knife," this week was either completely off the mark or (more likely) I was for however many weeks

For a while I was getting a lot of tracks I had already listened to on Spotify, which was odd. Just looked again now and this week's doesn't have that problem but mostly recommends me things from the most popular/indie end of the spectrum I listen to, i.e. things I've already heard of and decided I don't care about checking out.

Of course ilxors are a really hard section of the population to recommend music to!

i think the thing about recommendations for me is, i generally don't care about music unless it comes with a story, or a connection to someone i know. it's a way of changing yourself via another's love. like trying on a shirt i'd never imagine wearing but finding a way into it via the fact it was a gift from somebody special. the music "itself" without those conmections is just kinda... flat to me. usually. that's why i like music writing, and why i like friends who are passionate about music. radio can act as a sort of placebo via a DJ. anyway when spotify, or last.fm, or whoever, recommends me something it's just dry and it could be the greatest thing ever but is hard for me to latch onto.

yes, but if a recommendation gives you a song you've heard with friends but didn't know what it was at the time, that system partially serves the need. i see your point though.

i'm a massive introvert so i've always discovered music the hard way. these 'curated' services suit me pretty well, in that i no longer have to get off my arse and look for new music that's similar to what i like.

and, my friends and forums and fan sites all still exist, so it's just an additional way to find new stuff.

Spotify has an equalizer in the settings on iPhone!? how long's that been there? i thought they'd have shouted it from the rooftops.

What?!

yeah a few releases back! waiting patiently for the desktop version

we should start a Recommend Tracer Hand Some Music thread

the rest of this site works well for that but a personalized thread would be fun. i would review everything!

Anyone else following this spotify playlist Fresh Finds

https://open.spotify.com/user/spotify/playlist/3rgsDhGHZxZ9sB9DQWQfuf

updated every wednesday

non-personalised new music from unknown / emerging artists

i tend to skip through it, i.e anything that starts like dullard paste style 90s American indie rock - straight to next track. however it's worth going through for a few gems

this is my second week experiencing Fresh Finds - Meltybrains? a band from Ireland that i have been following for over a year are on this weeks playlist with their afrobeat-futuristic-electronic-art-rock-pop track Vine

take a listen:

Meltybrains? - vine
https://open.spotify.com/track/3JTW12iyImNivo7O6jSqsb

INSIDE SPOTIFY'S PLAN TO TAKE ON APPLE MUSIC
http://www.fastcompany.com/3049231/tech-forecast/inside-spotifys-plan-to-take-on-apple-music

It's called Fresh Finds. At first glance, it's just another playlist—it could easily be one of the collections hand-curated by Spotify's 32 music editors, or one of its 75 million users for that matter. But Fresh Finds is different: The weekly playlist is generated using a chunk of the predictive big data technology that Whitman and his team at The Echo Nest brought with them to Spotify last March. The mission of Fresh Finds is to identify under-the-radar artists that are generating buzz online and surface the ones most likely to break out.

"Fresh Finds is a distillation of the hippest users on Spotify," says Whitman, pulling up a list of 38 tracks projected against the conference room wall. "These are the artists that are going to break out soon because they're being listened to by these people."...

How does he know? The machines told him, naturally. Fresh Finds takes a central component of The Echo Nest's original methodology—its web content crawler and natural language processing technology—to mine music blogs and reviews from sites like Pitchfork and NME and figure out which artists are starting to generate buzz, but don't yet have the listenership to show for it. Using natural language processing, the system analyzes the text of these editorial sources to try and understand the sentiment around new artists. For instance, a blogger might write that a band's "new EP blends an early '90s throwback grunge sound with mid-'80s-style synthesizers and production—and it's the best thing to come out of Detroit in years." If this imaginary act goes on tour and writers in Brooklyn dole out praise of their own, the bots will pick up on it. It helps address an issue some people have voiced early on with Apple Music, that its selections aren't adventurous and it tends to recommend things you already like rather than things you might like.

After generating a list of talked-about artists, the Fresh Finds algorithm checks that list against the listening habits of a subset of Spotify's users that the system has determined are "ahead of the pack"—that is, the many thousands of very active listeners who tend to discover new artists before they break. In early, internal testing, Whitman and his team say that this approach, in addition to being clever, actually works. He shows me a collection of analytics charts that compare an artist's "buzz" factor (as determined by the blog-reading bots) with its listenership on Spotify. Sure enough, in many cases, a burst of online chatter about a new artist is followed by a spike in listening.

read the whole article..for all the details

I worry that if I listen to Fresh Finds, it might give me another shitty Discover playlist.

Wary of it due to the usual problem with centralised trend aggregating as described.

Highlighting curated playlists of new stuff (NOT divided by genre) from a range of individuals is preferable.

listening to a track once will not ruin your discover playlist, however if you only save the tracks you do like to another playlist then your discover playlist will likely improve

as explained further in the article

http://www.fastcompany.com/3049231/tech-forecast/inside-spotifys-plan-to-take-on-apple-music

Discover Weekly analyzes your own listening history, with an emphasis on what you've been bingeing on recently. It then takes that knowledge and compares it to the playlisting behavior of other users in the hopes of tapping into that distinctly human, gut feeling that dictates why one song sounds good following another or why this particular collection of 35 songs feels perfect for your mood on a given afternoon. Scanning millions of playlists, the system tries to find tracks that are commonly listed alongside the music with which you're already familiar, and then group those tracks together into a new, personalized playlist. Effectively, it takes the classic "people who like that also like this" logic of collaborative filtering and applies it to the process of making a mixtape for somebody.

This is kind of an obvious thing to do, but it's been entertaining me recently:

From the main everynoise.com map, go to the page for any genre and click on "List" at the top of the page. You'll get an embedded Spotify playlist of songs matching that genre. By clicking the </> icon in the embedded player's controller, you can copy the playlist link, open it in the web player or stand-alone app, and then follow that playlist. This is convenient for me because I usually listen to Spotify on my home sound systems or iPhone rather than on my computer.

Here's a playlist for "cool jazz" that seems representative: http://open.spotify.com/user/thesoundsofspotify/playlist/3RtFvzIXD7ulUCXkWdIOWW

How We Understand Music Genres is a good brief explanation, but I'd love to read a more detailed discussion of the data analysis behind Every Noise at Once.

More on Fresh Finds

Understanding the brand new
http://notes.variogr.am/post/125515460365/fresh-finds

by Brian Whitman

Scientist, sound artist, co-founder & CTO of the Echo Nest, Principal Scientist at Spotify.

“Fresh Finds” is made possible by a scalable analysis of the musical activity happening outside Spotify: daily, we automatically find artists people are talking about on music blogs and news sites more often and with more intensity than their playcounts should suggest. These are the artists that find fans through word-of-mouth, shows and the hard work of making unique music that connects to at least one person. We then filter those artists through a real time analysis of Spotify listening behavior and weekly generate a list of brand new songs that we think we will gain in popularity the next week.

The listener activity that happens to music deep in this brand-new, unheard part of the spectrum is hard to automatically understand. It comes from nowhere, and people discover it from other people, often outside of our platform. They read music blogs and press, or a friend in the know passes on a link. It’s not based on popularity or audio or likes or clicks. Some of these Fresh Finds had virtually no plays when data indicated we should publish them on the playlist. Watching a brand new artist release a brand new track with no connection or external push and seeing it at first slowly, then rapidly gain in plays on Spotify has been life-affirming.
I see recommendation, filtering, or prediction of this “brand new” as a new artistic frontier in music understanding. Every music data scientist wants to help artists and listeners, but the quantity of known good that a precise recommendation for a well known band earns all but vanishes when stacked up against the connection between a new unknown and her new fan base. I’m ecstatic to help that process even a little bit.

Brian Whitman's Favorite jams from the past 6 months of Fresh Finds:

Found on Fresh Finds playlist:
https://open.spotify.com/user/bwhitman/playlist/1EViHawT7ibM3pS2gPE4mW

Since Fresh Finds started working internally for us early this year, I’ve discovered more music there than from any other technology or web site or service I’ve ever used.

There are direct links to those The Sound Of playlists at the bottom of each genre page. Save you a few clicks...

Anyone else following this spotify playlist Fresh Finds

https://open.spotify.com/user/spotify/playlist/3rgsDhGHZxZ9sB9DQWQfuf

updated every wednesday

non-personalised new music from unknown / emerging artists

brilliant discovery! it's a proper lucky dip, and i'm enjoying at least half of this week's. fun stuff like this will keep me on spotify indefinitely.

There are direct links to those The Sound Of playlists at the bottom of each genre page. Save you a few clicks...

Aha, thanks.

So digging into Fresh Finds right now ... I like the idea.

Tracer Hands' post about music recommendation is, er, spot on for me as well. One thing I wonder is if music recommendation engines could do a better job going forward of unpacking WHY a song is recommended to you in some way -- beyond "you listened to X, you should try Y" which is a pretty shitty corollary. Like TH, I tend to be much more excited about a recommendation when I have why it was recommended to me explained a little. For something like Fresh Finds, it would be interesting if you could essentially see the blogs/reviews/Soundcloud momentum that, even algorithmically were responsible for putting into the list. Is that possible within the Spotify mobile app? Not sure. But if Spotify ever let other companies license their stream to build apps that house it, my sense is that some enterprising technology company could find a way to demonstrate this in quasi-infographic form, with little blurbs, factoids and so forth. The current of just seeing a list that says "Trust us -- we have some scientists and dudes with impressive beards" isn't really as powerful.