Detect duplicate MP3 files with different bitrates and/or different ID3 tags?

Question

How could I detect (preferably with Python) duplicate MP3 files that can be encoded with different bitrates (but they are the same song) and ID3 tags that can be incorrect?

I know I can do an MD5 checksum of the files content but that won't work for different bitrates. And I don't know if ID3 tags have influence in generating the MD5 checksum. Should I re-encode MP3 files that have a different bitrate and then I can do the checksum? What do you recommend?

Solution 1

The exact same question that people at the old AudioScrobbler and currently at MusicBrainz have worked on since long ago. For the time being, the Python project that can aid in your quest, is Picard, which will tag audio files (not only MPEG 1 Layer 3 files) with a GUID (actually, several of them), and from then on, matching the tags is quite simple.

If you prefer to do it as a project of your own, libofa might be of help.

Solution 2

Like the others said, simple checksums won't detect duplicates with different bitrates or ID3 tags. What you need is an audio fingerprint algorithm. The Python Audioprocessing Suite has such an an algorithm, but I can't say anything about how reliable it is.

http://rudd-o.com/new-projects/python-audioprocessing

Solution 3

For tag issues, Picard may indeed be a very good bet. If, having identified two potentially duplicate files, what you want is to extract bitrate information from them, have a look at mp3guessenc.

Solution 4

I don't think simple checksums will ever work:

1. ID3 tags will affect the md5
2. Different encoders will encode the same song different ways - so the checksums will be different
3. Different bit-rates will produce different checksums
4. Re-encoding an mp3 to a different bit-rate will probably sound terrible and will certainly be different to the original audio compressed in one step.

I think you'll have to compare ID3 tags, song length, and filenames.

Solution 5

Re-encoding at the same bit rate won't work, in fact it may make things worse as transcoding (that is what re-encoding at different bitrates is called) is going to change the nature of the compression, you are recompressing an already compressed file is going to lead to a significantly different file.

This is a little out of my league but I would approach the problem by looking at the wave pattern of the MP3. Either by converting the MP3 to an uncompressd .wav or maybe by just running the analysis on the MP3 file itself. There should be a library out there for this. Just a word of warning, this is an expensive operation.

Another idea, use ReplayGain to scan the files. If they are the same song, they should be be tagged with the same gain. This will only work on the exact same song from the exact same album. I know of several cases were reissues are remastered at a higher volume, thus changing the replaygain.

EDIT:
You might want to check out http://www.speech.kth.se/snack/, which apparently can do spectrogram visualization. I imagine any library that can visual spectrogram can help you compare them.

This link from the official python page may also be helpful.

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Comments

[David]

Also Picard is open source and MusicBrainz can be used by your own code.

[James McMahon]

Interesting, how does it Picard generate this GUID?

[Ishbir]

@James: in case you haven't found an answer to the question you posed in your previous comment, please see my previous comment here.