Maybe you are referring to some of the sites that use Spotify's API, like https://musicstax.com/ or https://tunebat.com/? The problem is that these sites often display inaccurate data. Although I haven't delved deeply into the issue, at first glance, it seems that what they label as "loudness" corresponds to momentary or short-term loudness rather than integrated loudness. Moreover, they do not provide true peak... Source: 12 months ago

With websites like songbpm.com and tunebat.com, you can look up the bpm for almost any song, which is great for musicians and to people who are just curious, but how do they determine only one bpm to display for a song with tempo changes? They don’t even tell you if the song has tempo changes, or what the other tempos are. For example, Bohemian Rhapsody has tempo changes in it, but it has been determined as 144bpm... Source: about 1 year ago

Https://tunebat.com/ does this. It’s made for DJs but it’s really good at recommending songs with a similar sound to the song you search. Source: about 1 year ago

I'll also use spotalike.com, and tunebat.com. Source: about 1 year ago

I want to search songs by bpm, key, genre etc. I'm aware of beatport.com but that only has EDM. There is also tunebat.com but it doesn't has the feature to search songs by genre. It would have been great if these websites allowed searching songs by language as well. Source: about 1 year ago

I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / about 2 months ago

Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / 2 months ago

The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 6 months ago

This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 6 months ago

Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 6 months ago