Deterministic batch renamer for DJ library tracks based on metadata tags and audio analysis.
Inspect metadata tags, detect messy names, and batch rename automatically or with manual inline edits.
Drop your audio tracks here or click to browse
Lossless (WAV, FLAC, AIFF) and Lossy (MP3, AAC, M4A) · Local Processing Only
Identify identical and alternate quality duplicate tracks in your collection.
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Detect exact duplicates (SHA-256) and acoustic matches with quality recommendations
Convert Rekordbox, Traktor, VirtualDJ and Serato collections 100% locally.
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Supports Rekordbox .xml, Traktor .nml, and VirtualDJ .xml
Transmute DJ USB drives between Pioneer, Denon Engine OS and Serato in-place without copying or duplicating audio files.
Transmutes existing DJ USB drives in-place without copying or duplicating audio files.
Connect or select your USB drive to inspect its DJ topology.
Pioneer, Engine Library and _Serato_ folders will be checked to provide cross-compatibility without touching your audio tracks.
Drag and drop audio files here or use the buttons below to import tracks.
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High-fidelity audio recording for microphones, DJ USB sound cards or system audio with peak and RMS metering
Compare the SHA-256 hash of every file, its duration and its tags to group repeated copies, get a recommendation for the copy to keep and export the plan. Everything is computed in your browser, without a single upload.
Four capabilities you can check in the code, not in a sales pitch.
Each file is read in full, hashed with Web Crypto and every file sharing that hash is grouped as byte-for-byte identical. The hash index walks the list once, so this tier does not slow down as the library grows.
The second tier blocks into one-second bins and only compares pairs whose duration differs by a second or less; inside each block it normalises title, artist and filename (mix labels, accents and punctuation removed) and scores them with Jaccard and Levenshtein, grouping anything that reaches 85 % similarity. There is no acoustic fingerprint: if two files sound alike but the tags do not match, this tier will not join them.
Every group scores its copies on quality tier (lossless, 320k or transcode suspicion), bit depth, sample rate, clipping, DC offset and tag completeness including ISRC. The highest score becomes the recommendation and you can replace it with your own choice per group.
Copies sit side by side with format, bitrate, sample rate, True Peak, LUFS, loudness range, clipped samples and file size; you can preview each one and hot-switch between them at the same point on the timeline. From your choice you download a CSV decision report and an archiving script bundle that starts in dry-run mode.
What this view solves before you load the USB stick.
The same track arrives as the label FLAC master and as a 320 kbps MP3 from a pool: duration and tags are nearly the same, so the group shows you both versions and you decide which one goes to the booth.
Several downloads of the same promo with an identical hash group themselves as exact duplicates, and the redundant-track counter tells you how many megabytes you can free up.
The plan collects the redundant copies and the recoverable space; download the scripts, run them in simulation mode and apply only the moves you actually want.
Between a WAV of doubtful origin and a 320 kbps MP3 with a clean cutoff, the quality score, the spectral ceiling and the clipped-sample count give you technical reasons to keep one.
Better to say it here than to find out halfway through a big clean-up.
This tool works on analyses already computed in your browser: the SHA-256 hash of the whole file, duration, title, artist and filename, plus the technical metrics — format, bitrate, sample rate, spectral ceiling, LUFS, True Peak and clipped samples — used to score each copy. There is no lookup against AcoustID, Chromaprint or any other external service, and the comparison never listens to the audio: two files holding the same song with different tags are only joined if they also share a hash.
We would rather publish them than have you discover them mid clean-up.
Candidate grouping uses duration and tags, not the audio signal. A remix with the same title and almost the same duration can enter the group, and two files of the same song with different tags will not be joined unless the hash matches.
SHA-256 needs the complete bytes and the quality metrics need the decoded audio, so the analysis does not stop at the headers: the bigger and longer the track, the longer it takes and the more memory it uses.
Resuming from the local cache restores at most 500 analyses. Each full result measures about 313 kB, so 20,000 tracks would be around 5.98 GB against a per-tab limit of 4,192 MB.
It only downloads scripts and a CSV: files move into _Duplicates_Archive when you run the script, in dry-run mode by default, without overwriting or deleting anything. Your choice of which copy to keep is not written to disk or to your DJ software either.
Metadata, library organisation and quality checks before you play out.
Why converting 128 kbps audio to WAV or FLAC never restores lost frequencies, and how to spot the phantom cutoff on a spectrogram.
Can you really hear the difference between MP3 320 kbps and lossless FLAC on a club PA? Psychoacoustics, transients and stereo phase.
Frequency axes, harmonics, dynamic range in dBFS and how to spot low-pass cuts before playing live.
ID3v2.4 tags, ISRC, artwork, duplicate detection and filename normalisation, step by step (Academy guide in Spanish).
Complementary utilities to organise and audit your library.
Bring tracks, findings and metrics of the whole collection together before and after the duplicate clean-up.
Check the frequency ceiling, LUFS and True Peak of each copy with an interactive spectrogram.
Normalise filenames with artist and title so the library does not fall apart again.
Export the cleaned collection to Rekordbox, Traktor or VirtualDJ keeping playlists and cues.
