One of the biggest problems faced by music application developers is song identification – that is – given an mp3 file, how can you accurately find the name of the song, album and artist? There are some hints in the mp3 file – the file name and the ID3 tags contain metadata about the track – but anyone who has worked with this metadata knows that this data is notoriously hard to deal with. The metadata is often missing, inconsistently formatted or just plain wrong. The result of this difficulty is that music application developers spend an inordinate amount of time just dealing with song identification.
Here at the Echo Nest we want to make it easy for developers to create music applications so we really want to solve the music metadata problem once and for all. That’s why we’ve created music fingerprinting technology. Today, we are starting to release it to the world.
The Echo Nest music fingerprinter takes a bit of music such as an MP3 and identifies the song based solely on the musical attributes of the song. No matter how messy the metadata is, the fingerprinter can identify the song since it relies on the music to do the identification. On his blog, Echo Nest co-founder Brian Whitman dives into the technical details of the Echo Nest Musical Fingerprinter.
- Very fast – under a second to ID a track
- Very accurate – uses Echo Nest music analysis technology at the core. (we hope to publish some data on ENMFP accuracy real soon)
- Open Data – all of the mapping of fingerprints to songs is open data. Anyone can get the data
- Open server – all of the server code is open – you can host your own FP server if you wish
We want to make sure that anyone who takes advantage of the EN Fingerprinter participates fully in the ENMFP ecosystem – and so it is licensed so that anyone who uses the fingerprinter technology will share their FP/song mapping data with everyone. No walled gardens – if you benefit from the ENMFP you are also helping others that are using the ENMFP.
It is still early days with the fingerprinter – we are doing a soft release. If you want to experiment with the ENMFP and you are at the Amsterdam music hackday this weekend send an email to firstname.lastname@example.org with your intended use case. We will get back to you ASAP with a link to libraries for Mac, Windows and Linux.