Comment by johanvts

9 days ago

Spotify is still bad for classical music because you can’t ex. search by composer or label of find alternative recordings of the same piece etc. If you know what album you want already its ok, but if you like classical you should really consider IDAGIO.

And if you want one subscription for popular & classical music, Apple Music is miles ahead of Spotify.

Music.app is already better than Spotify at handling the relevant metadata. But the dedicated Apple Music Classical app is roughly the same as IDAGIO.

(They bought IDAGIO's former competitor Primephonic to do it)

Isn’t fundamentally the issue that for any symphony by Beethoven or whoever that there are thousands of recordings of performances? So if I decide I want to listen to a certain one then I also need to pick a particular performance that a particular orchestra did a certain time?

  • Apple Music has a totally separate app for classical music. It was specifically designed to address exactly this.

    For each composer, it shows all their well known works, and then you can tap on each to see all the recordings of that particular piece.

    Smart move on Apple’s part, if you ask me.

    • As mentioned above, they bought Primephonic, which already had all those features. For myself, I used Primephonic until Apple bought it, then switched to Idagio, in order to minimize my connection with the Apple machine.

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    • I love that app. They have Dolby atmos mixes which seem like overkill but I was completely floored putting on a double bass work and being completely immersed in the center of the sound. Obviously great for large ensembles but surprisingly awesome at solo works

      And the play history integrates with the main Music app

building recommendation systems for classical music has a simple data problem- most recommendation systems (for spotify and others) are based on simple user listening histories that look at "people that listened to X also listened to Y".

this is a problem for classical (and jazz) for two reasons a) these genres are not particularly popular on the platform so there are few unique users and b) the songs are LONG so listening sessions contain fewer songs.

track cooccurance based recs work well for popular genres, but these other genres need a different approach to recs and that's actually where AI could do really well by digging into the unstructured data associated with the tracks (sonic analysis of the song, biographical information about the composer, details about featured soloists, etc) rather than relying on piles of user behavior.