I am sorry, I was not thinking and just assumed the software was known, that is my bad.
Yes, you found the proper software. I understand that using Shazam is not the most ideal solution, as you stated. I refer simply to the functionality. There is an alternative to Musixmatch (which might provide their fingerprinting recognition portion in addition to the lyrics?) called AudD (https://audd.io/), and MB uses AcoustID, which at face value seems to be at least similar. There is an implementation using this called Mousai (GitHub - thwaller/Mousai: Identify any songs in seconds).
The above is all part of what prompted my interest in AcousticBrainz, wanting to play around with more and different to identify music. I found many times I could use this on my old volumes of MP3 files, which when they first came around, were not properly structured or organized into albums. After hearing your statements, there is overlap, here is example on two different uses:
- I have a “album” of audio files. While it is not a real album, I can identify which album(s) it might most closely resemble… helping me turn the mess into a structured set, and
- Take my unstructured messes and help me identify what other music could be added to correspond to the style I have in my messy collection.
An example fitting the above, which I see as common… I have a set of say 20 files, of the most popular recordings from an artist (sort of like a custom Essentials, Greatest Hits, etc) and I have a few other recordings of similar artists and maybe some that my main artist if a featured artist on. What this additional functionality can help with is directing me to maybe that primary artists real greatest hits release, releases from the artists said artist was a featured artist with, and other artists on similar style and interest. This can help me turn a random set of files that might my like a favorite customer CD into a respectable playlist that I might be able to not only collect but also import to my Spotify or YouTube music subscription.