How to easily calculate the Beats Per Minute (BPM) of a song

Knowing the  Beats Per Minute (BPM) of a song can be very useful

• If you are a runner matching the BPM to your running pace can help improve your performance.
• Professional DJ's need to be able to blend the end of one song into the next, without the transition being awkward or jerky. By figuring out the BPM  you'll  know if you need to bring the tempo up or down to have them both playing at the same speed.
• Creating a  playlist to fit a certain mood is considerably easier if you use songs with a similar BPM

But how do you actually calculate it ?

There is now a really easy way to do this thanks to a new project called  AcousticBrainz 
a collaboration between MusicBrainz and Music Technology Group, University of Barcelona

• First your songs needs to have MusicBrainz Recording Ids, as you know this is easiest to do by running them through SongKong Tagger 
• Then download an AcousticBrainz client from here
• Install and run the client and point it to your music collection, this will calculate the BPM for each song and then submit it anonymously to AcousticBrainz
• Then to look up the BPM just look up the page http://acousticbrainz.org/mbid in your web browser i.e. http://acousticbrainz.org/5f3a763a-669d-4a4c-bafa-d76fc5ae885d
• You'll notice it doesn't just provide the BPM but all kind of cool things such as key, danceability and mood , but more about these in another post.

The future

This is a brand new project so it is not integrated into any other tools yet but soon SongKong and Jaikoz will allow you to both submit new AcousticBrainz data and to automatically add it to your songs.

Matching Multiple Albums using only Acoustids

The SongKong 3.4 release is full of improvements to the matching process.

SongKong now does a much better job of handling multiple albums without metadata in one single folder. Previously if you had Only allow match if all tracks in album were matched enabled it had difficulty matching multiple albums contained within a single folder unless they had some existing metadata. The workaround was to disable the option but this then allowed SongKong to match partial albums, possibly not the desired outcome. Now in this release SongKong can derive metadata from the songs Acoustids and group and match the songs accordingly without having to disable the above option.

Overall SongKong is better at matching albums, before this release it would try and match a grouping completely to one album, if that failed and depending on user preferences it would then match each song one by one. Now before resorting to song by song matching it trys matches partial groups to a release. This means results are split over less albums, and it speeds up the matching process because it is quicker to match a group  of songs to a release in one go rather than song by song.

There are some super larger releases in  MusicBrainz and Discogs, these are usually Box Sets of the complete works of established artists. Matching songs to these larger releases can be time consuming and give the impression that SongKong has stopped working. A number of improvements have been made to prevent SongKong spending too much processing a group of songs, and a Still Alive progress bar has been added to show that SongKong is still working 

Full details of all issues fixed in this release can be found here .

New Version of SongKong with Better Matching

Today on 3rd November 2014 we release SongKong 3.3, this release is full of improvements to the matching process:

SongKong now does a much better job of matching songs to multi-disc releases such as box sets, previously if checking against very large releases such as this 50 Cd Elvis Presley Box Set SongKong could take a long time, now the matching is quick and accurate.

Match Song to Recording only is now more effective at identifying the correct song when an acoustid matches to multiple recordings because it takes existing metadata into account.

Discogs matching is more effective because SongKong can now find matching albums based on the existing song titles in your files, before potential albums were only found based on existing artist and album name metadata.

We have also improved the identifying of duplicates when matching songs by taking into account acoustids and song title metadata at the same time. By identifying duplicates files we can better match the non-duplicates files to the correct album.
Full details of all issues fixed in this release can be found here .