I highly recommend Musicbrainz Picard: https://picard.musicbrainz.org/

It will match against the Musicbrainz database and will acoustically ID your files, so the tags can be completely wrong and it can ID the song from it's sound fingerprint. Just dump folders of albums into the client, it will group and sort things and ID them. It works great.

I only wish it wasn't written in Python - writing good GUI apps is way too hard with it, also the lack of static typing makes development of anything beyond simple scripts a potential minefield.

I wish there had been something like MusicBrainz but for movies, they now have BookBrainz[1] so that would have covered most aspects of digital content.

[1] https://bookbrainz.org/

It's a miraculous project. I have something like 300+ albums from 170+ artists and it tooks me only a few days to cleanly retag everything, with about 99% of the albums just working.

I'll 2nd Picard. Been using it for years (and contributing to musicbrains for years).

Musicbrainz Picard: highly recommended

> It will match against the Musicbrainz database and will acoustically ID your files, so the tags can be completely wrong and it can ID the song from it's sound fingerprint.

For songs that have covers, it will ID the song as any of a number of similar covers. I just tried to use it to tag something from the Grease 2007 revival soundtrack (which, as of this writing, doesn't exist in Musicbrainz), and it happily identified it as the same song from the 1994 revival, which is wrong. This makes me hesitant to use it to identify songs if I don't already know what the identification should be.