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Tuesday 15 December 2015

Finding the mood of a song


Finding the mood of a song

Playlists let us group songs in a way that is meaningful to use instead of the traditional approach of listening to songs album by album as directed by the artist. So many of us have large music collections these days that playlists are becoming increasingly more important way of categorising our music.

One way of categorising music is by considering the ambience or mood of the song. Clearly you would aim for a different ambience for a  romantic evening at home then for a house party!

Manual Mood Identification 

The original way to do this would be look at your songs and manually select them based on their mood. But its difficult to do this for most songs without actually listening to them, and most of us don't have time for this anymore.

Automatic Mood Identification

Its now possible to use computers to listen to the songs and extract various acoustic attributes, then by plotting multiple attributes against each other a mood can be worked out.One way of defined mood is by considering two acoustic attributes: Energy and Valence.


Represents a  measure of intensity and powerful activity released throughout the track. Typical energetic tracks feel fast, loud, and noisy. For example, death metal has high energy, while a Bach prelude scores low on the scale.


Describes the musical positiveness conveyed by a track. Tracks with high valence sound more positive (e.g., happy, cheerful, euphoric), while tracks with low valence sound more negative (e.g. sad, depressed, angry).

Combining these two on a graph is a strong indicator of acoustic mood,for example a song with high arousal and high valence could be defined as delighted, whereas one with high arousal and low valence could be defined as angry. Low arousal and low valence may be bored, but low arousal and and higher valence could be content. This methodology is used by companies such as Echonest for the Spotify site.

SongKongs way of doing things

SongKong Pro also uses the Energy/Valence algorithm, built on top of the data provided by  AcousticBrainz , these are the same guys who already provide BPM data. When a MusicBrainz song is identified by SongKong we can then lookup the acoustic attributes and calculate the mood. The mood is then stored in the standard mood metadata field so it is available to other applications.

Because the acoustic attributes have already been calculated for millions of songs your computer  doesn't have to actually analyse the song itself. This computationally hard work has already been done

Because the AcousticBrainz is already stored in the JThinkMusicServer we can get this information at the same as we get everything else, meaning no additional time is spent getting these new acoustic attributes.

We also add some other acoustic attributes that we will talk about more in another post

Friday 20 November 2015

Adobe Lightroom or Photoshop - SongKong versus Jaikoz

Lightroom versus Photoshop

I have used Adobe Photoshop on and off for many years for photo editing. It is an incredibly powerful tool for photo-editing that offers limitless opportunities, but that is part of its problem. You can easily spend an afternoon working on a single photograph to get it perfect. And because I did not use it regularly often I did not use it in the most efficient cleverest way.

I also used Apple Aperture for managing my photographs but found it awkward to use not least because of the opaque library it uses in a similar way to how iTunes manages songs. But then I discovered Adobe Lightroom - at first it replaced Aperture offering a much clearer way of managing my photographs and making simple adjustments such as contrast and exposure and white balance. But then as I delved into it I found almost everything I used Photoshop for could be done in  Lightroom , and it was more obvious what to do and the results were often better.

One particular aspect of Lightroom that I love is that instead of having to use layers to ensure I dont modify the original photo I do not even have to think about it, Lightroom never modifies the original photograph instead all changes are written to its catalog and can be undone.

And I never have to think about working colour profiles either, I only have to worry about colour profiles when I export the photograph for use in another application or print.

I still use Photoshop because it can do things that Lightroom cannot, but most of the time I just Lightroom.

So why am I telling you this in the jthink blog ?

Firstly, I have just launched my Secret Dorset Photography website, would be great if you come and  took a look

Secondly, because the analogy between Lightoom and Photoshop is very similar to how I feel about SongKong and Jaikoz.

SongKong versus Jaikoz

Jaikoz development started in 2006 which coincidentally seems to be when Lightroom development began. But in this story Jaikoz is more analogous to Photoshop, from the start it has added manual editing and automatic matching . There are more than one way way to do some tasks and I have also been receptive to user enhancements requests to try and solve every possible problem. I think Jaikoz offers more comprehensive tagging than any other music tagger on the market.

But this complexity comes at the cost, although Jaikoz can be used simply this is not immediately apparent to users

SongKong is only two years old, the aim was to provide powerful automated matching with a clear workflow for the user. SongKong does not offer manual editing and never will, there are now many tools to do that. SongKong does not try to emulate all of the Jaikoz automated matching functionality just the most useful stuff.

For example MP3s support three versions of the ID3 tagging standard v22, v23 and v24, and Jaikoz supports saving with all three versions. But nobody uses v22 anymore, everything supports v23 and many applications now support v23. So SongKong just supports saving v23 and v24 we have lost a tiny bit of functionality for more simplicity, nobody has complained about this so far.

Now lets try to stretch the analogy to Photoshop layers . Unlike many other tag editor tools Jaikoz doesn't save changes as they happen instead everything is done in memory and can be reviewed before the modifications are saved. This is much safer but it does put the onus on the user to check the modifications, and can mean a delay if many file need to be saved at the end of an editing session.

With SongKong I wanted to remove this burden from the user, but just having SongKong making changes without the user having an opportunity to reverse the changes was dangerous. So instead all modifications are written to SongKongs database similar to the way edits are written to Lightrooms catalog. Unlike Lightroom the files are modified as well but because the changes are written to the database they can be undone at a later date, no problem.

These days my first point of call for cataloging my music is SongKong, I then use Jaikoz for songs that SongKong fails to match plus for special tasks such as exporting metadata to a spreadsheet.


For my photographs I need both Lightroom and Photoshop but I get much more use out of Lightroom. For my own music I need both SongKong and Jaikoz but songs always go through SongKong first.

Hope this helps with your decision making

Wednesday 4 November 2015

What's the best lossless format?

What's the best lossless format?

Most of us know that generally lossless is better than lossy because it retains all of the audio and therefore sound better, and you can also convert form one lossless format to another without losing any sound quality. Lossless does require significantly more disk space but his doesn’t mean you have to reduce the amount of music stored on your iPod, iPhone or mobile device. For example iTunes allows users to convert higher data rate music files to 128kbps AAC on the fly as the music is synced to the mobile device in question. 

But what Lossless format should you choose ?

Currently there are four widely available choices:
  • Aiff
  • Wav
  • Apple Lossless
  • Flac


WAV is a music file format developed by Microsoft and IBM capable of storing Linear PCM audio (the digital encoding format used on compact discs) in completely uncompressed form. Ripping a CD and storing it as an uncompressed WAV results in “bit perfect” storage; the ripped music file is identical to the original CD data package. WAV files can also store high-resolution music files at greater bit depths and sampling rates than CD’s 16-bit/44.1kHz resolution. Uncompressed WAV files can be ripped and played back in iTunes and are very high quality. However, they do take up more hard drive storage space then lossless compressed formats such as Flac or Apple Lossless

WAV files originally did not support metadata, there is now defacto support using ID3v2 - the same format that is used by Mp3s. However not all players and tools currently recognize ID3v2 metadata in Wavs.


AIFF was developed by Apple and is very similar to WAV. Again it is capable of storing uncompressed Linear PCM audio. Ripping a CD and storing it as uncompressed AIFF results in “bit perfect” storage with the ripped music file identical to the original data on the CD. Like WAV files, AIFF files can also store high-resolution music files at high bit depths and sampling rates. 

AIFF uses ID3v2 like Wavs and Mp3s. ID3v2 metadata is within Aiff is much more widely recognized - notably it is properly supported in iTunes.

Apple Lossless

This is a newer Apple file format option that employs lossless compression, which reduces the stored data to as little as half of the original music file’s size but restores bit-for-bit identical to the original music file on playback. The process is not unlike a zip file in which a large amount of data is “zipped” down to a smaller file size for storage and “unzipped” to its full size when opened.

There is discussion about whether uncompressed  music  files  such  as  WAV  or AIFF can sound better than lossless compression formats like Apple Lossless or FLAC because they don’t require the additional  step  of  being  “unzipped”  and  restored  to  their  original  PCM data package during real-time during playback, but this difference should only be noticeable in older and slower hardware.

Apple Lossless offers full metadata support using its own metadata format, this metadata format is also used by Apples lossy Advanced Audio Coding format. Both formats can be found using the .mp4 or or .m4a format which can be confusing

FLAC (Free Lossless Audio Codec)

FLAC is an open source lossless compression format similar to Apple Lossless Compression, this reduces the stored music file’s size, but then restores the data package bit-for-bit identical to the original music file on playback. It supports high-resolution audio with greater bit depths and sample rates and also supports metadata tagging using Vorbis Comments.

The main problem with FLAC is that although it is  an extremely common and accepted format, it is not supported by iTunes and Apple hardware such as the iPod.


 I would love to recommend the open source FLAC format but because of its poor support in the Apple ecosphere  I don't think it is currently the best choice, particularly since Apple punches above its weight when it comes to digital music.

Although Wav audio format is well supported, support for its metadata is poor so again I would not recommend Wav.

So we are left with two Apple formats. With Apple Lossless we get a smaller filesize and good metadata support, with Aiff we get a larger filesize but even better metadata. Both are well supported on Apple and non Apple hardware and software. The ID3v2 format used by Aiff format has been around a long time (because used by Mp3 as well)  and although it is a little unwieldy it is well understood and very powerful, the metadata format used by Apple Lossless is not as well understood or flexible.

Everybody circumstances differ but for me the current best choice is Aiff

Jaikoz 8.4.0 now with full Aiff and Wav support

 Jaikoz 8.4.0 now supports reading and writing metadata to Aiff and Wav formats !

Aiff and Wav Support 

Aiff and Wav formats each provide an uncompressed lossless format for your audio and were created in 1988 and 1991. However until more recently there was no agreed way to store anything but the bare minimum of metadata, this is why we originally didn't add support within Jaikoz. The other reason was these formats were expected to die out and be replaced with newer formats but although they are less prevalent then before this has not happened.

However we revisited these formats and discovered that defacto support for Aiff tagging and Wav tagging now existed using an ID3v2 chunk, just like MP3 files. Because they use ID3v2 they can now store all the metadata that Jaikoz finds such as artwork, composers, bpm and  MusicBrainz and Discogs identifiers - not just the basic metadata such as artist and album.

This also means you can edit your Aiff and Wav metadata not just with the Edit tab but also using the ID3 Edit tab. The ID3 Edit tab shows hows exactly how the fields are stored and also gives access to any additonal ID3 fields that are not mapped to a generic field in the Edit tab.

You can also decide on the ID3v2 format to use, by default they will use the value of Preferences:Save:ID3Tag V2:Write V2 Tag Version

But you can override this for any individual file by selecting a different value from the
Version column.

Single Song Matching

We also make some improvements to single song matching. Single song matching occurs when a song has been not been grouped with any others songs or no match was found for the group of songs and user preferences allow Jaikoz to try and match each song individually. Because only one song is being matched any album containing the song is a potential good match but we have made some changes to find a match for an original album rather than a compilation whenever possible.

Full list of fixes is as follows:


  • [JAIKOZ-1070] - Should not bother trying to do release metadata match unless have artist and release
  • [JAIKOZ-1079] - Saving Acoustids gets confused if filename has been modified but not saved
  • [JAIKOZ-1085] - Too many files exception when matching


  • [JAIKOZ-290 ] - Add support for AIFF format (which might use ID3v2 format for metadata)
  • [JAIKOZ-1071] - When have no metadata single song matching do more to find track AND artist
  • [JAIKOZ-1074] - SingleSong match should first match by artist+title+release if have data
  • [JAIKOZ-1075] - SingleSong matcher should filter out Compilation acoustid matches
  • [JAIKOZ-1083] - Add support for Wav with RIFF
  • [JAIKOZ-1088] - Make artist and track search fuzzy match tracks

Tuesday 13 October 2015

Aiff and Wav tagging now available

SongKong now supports reading and writing metadata to Aiff and Wav formats !

AIFF and WAV formats each provide an uncompressed lossless format for your audio, whereas Flac and Apple Lossless provide a compressed lossless format. Both types can encode your audio without losing any of the original data. An uncompressed format does not need to be uncompressed during playback, which can potentially result in smoother playback but at the expense of larger file sizes, however with most hardware it is unlikely you could detect any difference in playback . To confuse matters a little it is now possible to store compressed lossless in Aiff and Wav files as well - but this is rarer and not part of the original specification.

Audio Interchange File Format (AIFF) was developed by Apple Inc. in 1988 and is most commonly used on Apple Mac systems. Waveform Audio File Format (WAV) is a Microsoft and IBM audio file format standard for storing an audio bitstream on PCs developed in 1991. Both are version of the Interchange File Format (IFF) format developed by Electronic Arts back in 1985.

All formats provide a way of storing data in chunks - however until recently there was no agreed way to store anything but the bare minimum of metadata, this is why we never added support within Jaikoz. The other reason was these formats were expected to die out and be replaced with newer formats but although they are less prevalent then before this has not happened.

However we revisited this and discovered that defacto support for aiff tagging and wav tagging now existed using an ID3v2 chunk, just like MP3 files. Because they use ID3v2 they can now store all the metadata that SongKong finds such as artwork, composers, bpm and  MusicBrainz and Discogs identifiers - not just the basic metadata such as artist and album. Wavs can store metadata in an ID3v2 chunk and also some basic metadata in an INFO chunk: for maximum compatibility with older applications SongKong adds both an ID3v2 and a INFO chunk to files when they are saved.

After a period of development and testing support has now been added to SongKong 3.18 and this is available from today, plus as usual we have some matching improvements and some additional fixes.

Support for these new formats will be added to Jaikoz within a few weeks.

Tuesday 8 September 2015

Jaikoz Automatic Music Tagger New version - 8.3.5

Just a small release (8.3.5) to fix some recently found bugs in Jaikoz with song identification
  • [JAIKOZ-1065] - Query by tracks needs an upper limit on how many tracks can be queries in one query
  • [JAIKOZ-1067] - Invalid attempt to get recordingId rather than trackId for Discogs check
  • [JAIKOZ-1068] - IsGoodArtist check not working well when comparing colloboration to one artist

Monday 7 September 2015

Awesome song identification with SongKong 3.17

Over the Summer months we released new versions of Jaikoz, culminating with the ultimate song identification

Now we have put all those improvements into the latest version of SongKong - and we release it today, we have even squeezed in a few more improvements that are not yet in Jaikoz.

We have also had the Spanish and German in program translations reviewed and corrected by professional translaters, if you find any issues  just let us know.

Now we are really keen to get support for new audio formats and new features into both SongKong and Jaikoz over the coming months.

The full list of fixes can be found here

Thursday 20 August 2015

Jaikoz 8.3.4 Released

We have just released Jaikoz 8.3.4

This release fixes an issue with Discogs matching plus two others:

[JAIKOZ-1009] - Export to xls exportsComent language for Xls causing problem for Import
[JAIKOZ-1059] - OSX:Error opening files in Finder with right-click unless Jaikoz already running
[JAIKOZ-1060] - Incorrect check being done for Discogs matches 

Sunday 9 August 2015

We've done it:Ultimate Song Identification

A couple of months ago long time Jaikoz user Alfg reported song identification was not working as well as in the previous major version. We did some investigations and quickly found a couple of issues that increased the number of songs identified.

But there was still some songs that were in the MusicBrainz database and a few songs that were being misidentified. It got me thinking is it possible correctly identify every single song if its in the database, and not misidentify any.

It is a difficult tightrope to walk trying to identify more songs where there is not a clear answer, ensuring we do not misidentify songs, because this is worse than not identifying the song at all.

It has taken a few iterations but now with Jaikoz 8.3.3 for these particular tests we now have 100% correct matches and no mismatches for a series of essentially random folders.


I realize not all our customers will have such success but I think most of you will be very happy with the improvements we have made, now I need to incorporate some of these improvements into the next version of SongKong.

The improvements we made in this release are as follows:

  • [JAIKOZ-1043] - isGoodArtistAndTitleMatch failing artist which just has additional 'the' in name
  • [JAIKOZ-1044] - Single song match doesnt do release match if metadata has song title
  • [JAIKOZ-1047] - ManualCorrect isAcoustid checkbox is never set
  • [JAIKOZ-1048] - Discogs matching should enable track duration check
  • [JAIKOZ-1049] - Only allow recordings with same name AND SIMILAR DURATION to one with most sources
  • [JAIKOZ-1053] - Matching to multidisc release can fail to match disc 2 because false match on disc 1
  • [JAIKOZ-1054] - Simplify album names when trying to find releases by metadata
  • [JAIKOZ-1057] - Try harder to find artists when grouping songs that have no artist

Wednesday 29 July 2015

More Jaikoz matching improvements with Jaikoz 8.3.2

Jaikoz 8.3.2 Released 

 Some more tweaking to the song identification algorithm plus fixing some recently discovered bugs and we have another new release:


  • [JAIKOZ-0999] - Error with highlighter when drop folder into Jaikoz
  • [JAIKOZ-1037] - NullPointer with HighlightDuplicateMusicBrainzUniqueIds
  • [JAIKOZ-1039] - java.util.NoSuchElementException in ArtistTitle check
  • [JAIKOZ-1040] - OSX:Error copying album artwork directly from Google Chrome


  • [JAIKOZ-1023] - What do do if tie and onlyUseRecordingWithMostSources enabled
  • [JAIKOZ-1029] - Ignore track duration check if track was already matched by Acoustid
  • [JAIKOZ-1034] - Double check songs by metadata only matches checking artist and title
  • [JAIKOZ-1035] - Increase artist/title check for single song metadata match

Friday 17 July 2015

Not so perfect

Okay, a little regression slipped into the 8.3.0 release but now fixed and deployed in Jaikoz 8.3.1

  • [JAIKOZ-1033] - Artist/title double check for single song metadata matching is incorrect

The Perfect Song Matching Algorithm ?

The quest for the perfect matching algorithm continues, but we are certainly getting closer. With newly released Jaikoz 8.3.0 we have made many improvements to the matching process.

We now do more to groups songs correctly and find possible potential releases, such as searching for releases by track titles if no matches found by release title.

And we are now stricter about accepting a match, we have added some additional checks to ensure it really is a good match.

So the match rate is now higher, and at the same time incorrect matches are kept to a minimum.

  • [JAIKOZ-773] - Allowing Acoustid matches when metadata exists but is bad
  • [JAIKOZ-1005] - If artist name contains feat and get no matches strip out and try again
  • [JAIKOZ-1007] - When single song matching against Acoustid ensure we are selecting the correct song
  • [JAIKOZ-1013] - Dots not removed from filepath when after path separator
  • [JAIKOZ-1014] - When disc has more than two discs may not match because can match songs to wrong disc
  • [JAIKOZ-1018] - Ignore join phrased when matching artists
  • [JAIKOZ-1020] - Consider artist name when doing track scoring
  • [JAIKOZ-1022] - Always only use recording with most sources when single song matching
  • [JAIKOZ-1024] - Extend Acoustid title check to an artist check
  • [JAIKOZ-1026] - Additional processing when songs organized one folder per artist
  • [JAIKOZ-1027] - Search by metadata should search by artist and tracks if no match on release

Thursday 9 July 2015

Better song identification with Jaikoz 8.2.5

In this release we have spent some time working out why some songs by Jaikoz do not get matched even though they exist in the Albunack database and we found a few bugs and improvements we could make.

  • [JAIKOZ-1003] -         Single song matching only matching by acoustids
  • [JAIKOZ-1004] -         Single song matching by Acoustid should only use recording with most sources
  • [JAIKOZ-1005] -         If artist name contains feat and get no matches strip out and try again
  • [JAIKOZ-1010] -         Unable to create fingerprints on Windows if filepath greater than 260 characters

So now you should get an even better matching rate with Jaikoz, already we believe have the most sophisticated and accurate matching algorithm out there, if you know any different let us know.


Monday 29 June 2015

Better song matching for songs of random folders with Jaikoz 8.2.4 Music Tagger

Jaikoz 8.2.4 released June 29th 2015

A new release of  Jaikoz with an important fix

Jaikoz relaxes its matching criteria if it detects a folder that  contains songs not limited to one album and artist. Whilst you may have some of your songs organized one folder per album its not uncommon to have  folders containing songs from all kind of sources in no discernible order, fixing these in Jaikoz is why you bought it in the first place, right ?

If Jaikoz identifies such a folder it relaxes its matching criteria so even if Only Match all songs to one album if all songs in grouping were matched is enabled it is ignored allowing these songs to be matched without breaking up folders that have already been organized

But there was a bug preventing it properly matching songs in such a folder even if the option was disabled. Now with this fix it does its matching correctly for these types of folders, even if the option is enabled. So you should now get much better results when trying to match such folders.

Thursday 18 June 2015

Reports, Error handling and iTunes improvements with SongKong 3.16

We have a new release of SongKong, version 3.16 !
This is a small release with some bug fixes and minor improvements

iTunes integration

This release fixes two issues with SongKongs iTunes integration:

SONGKONG-863:OSX:Error when unable to find track in iTunes

Error Handling

Usually SongKong can be run on any number of files without memory issues, but badly behaved images can cause a memory issue. SongKong was not recovering from this error and if the memory issue did reoccur when loading songs SongKong was not reporting the error correctly, this is now resolved. 

We have added a new option for reports. This option can be used to prevent the report being opened automatically, the report is still created and can be opened immediately after processing from the summary panel or from the Reports menu.

SONGKONG-869:Progress Dialog should close automatically once finished processing

Once SongKong has finished a task such as Fix Songs it now automatically closes the progress dialog, previously it had to be manually dismissed.

SONGKONG-375:If user has disabled Discogs searching AND Matching dont show Unmatched Discogs section

The dialogs have been tidied up so that they do not show Discogs counters when the customer is not trying to match songs to Discogs.

Discogs Artists that could be linked to MusicBrainz Artists Report

Within MusicBrainz it is possible to link an artist to the equivalent Discogs artist, in fact there are already some 300,000 artists linked. However there are nearly a million artists within MusicBrainz leaving nearly 700,000 artists unlinked, the majority of these already existing in Discogs.

Linking both artists together allow information between the two databases to be shared, for example the Discogs artist may contain the real name of the artist and that might be missing from the equivalent MusicBrainz artist aliases. Alternatively MusicBrainz may have various translations of an artists names for different languages, and these variations may not be available in Discogs.

Albunack now contains a number of reports that attempt to find potential matches between the two together with a link for each match to make it easy to add a link from MusicBrainz artist to the Discogs artist, all listed here

The first report  MB artist matches Discogs artist and both have a release with same name and the artist names are unique contains over 40,000 potential links. Matches are only listed here if the following criteria are met:
  • Simplified MusicBrainz artist is unique within MusicBrainz list of artists.
  • Smplified Discogs artist name is unique within Discogs link of artists.
  • Neither name is already matched
  • Both the MB artist and the Discogs artist have released an album with the same name
Because of these conditions we are confident there are very few (if any at all) bad links.

The simplified artist names remove case, accents and some punctuation in order to allow matches between artist names that are not identical. Because we only include artists whose simplified name is unique within the databases it is unlikely that the MusicBrainz artist has linked to the wrong Discogs artist. And this is made very unlikely with the last condition that requires both artists to have a release with the same name.

Some of the links may already have already been created because the underlying database is not updated in real time, but it is regularly updated - usually every week.

Links are listed so that artists with the most releases are listed first, the basis being that these are likely to be of most interest.

But with 40,000 artists to link the job to complete this task could take some time, so if you have 10 minutes please consider double-checking and then creating some of these links within MusicBrainz.

Friday 12 June 2015

Linking a Discogs release to a MusicBrainz Release

Linking a Discogs release to a MusicBrainz Release

In the past there have been two significant problems with trying to link Discogs releases to MusicBrainz release.

Finding a release

Firstly, it was difficult to Discogs release that can be linked to MusicBrainz but aren't already. You could browse an artist releases on Discogs but there is no indication on the Discogs site as to which ones are already linked to a MusicBrainz release. You can check whether an individual release on MusicBrainz is linked to the Discogs but you cannot filter a list of releases by whether or not they are already linked. 

And when popular artists can have hundreds of Discogs releases linked to a single master, and even moderately popular artists can often have more than thirty it is difficult to find the correct release to link to if any. Working out the best match is difficult when having to consider and compare differences and matches in metadata such as track lists, catalogue nos, barcodes, country of release and record labels.

Linking the Release

Secondly you have to actually add the link. 

Linking the release is not so difficult but when the Discogs release contains extra information that the MusicBrainz release does not have, wouldn't it be good to get that data in as well, but adding that extra data for more than a few releases at a time is time-consuming.

Linking a Discogs release to a MusicBrainz Release with Albunack

Today I am going to show you how to easily link Discogs releases to MusicBrainz releases with Albunacks artist-centric approach solves both of these problem

Finding a Release

Albunack combines data from both databases to provide comprehensive combined Artist discographies.:
  • Information from MusicBrainz and Discogs is combined on a single page.
  • Release group, Release and Track listings are all available on a single page.
  • Existing links between MusicBrainz and Discogs are shown
  • Potential matches identified by Albunack are shown. 

Linking a Release

When you click on the link button Albunack not only links the two releases but adds additional data such as barcodes and catalogue nos, you simply have to check the data and then click submit.

We have created a video to show exactly how this is done

Introductory video added to Albunack

The JThink Music Server is a dedicated server that contains MusicBrainz and Discogs data, and  is what Jaikoz and SongKong use for their automatic matching. Albunack is the public face of the music server and can be used to browse combined MusicBrainz/Discogs discographies for almost any artist.

If SongKong is not finding a match when you think it should, it is probably easier to check on Albunack instead of MusicBrainz or Discogs. Although note Albunack doesn't currently show collaborations or Various Artist releases (although they are in the JThink Music Server).

Two months ago we released Albunack and now we have now added  a Youtube channel , and this includes an introduction to Albunack

this gives a nice overview on how to navigate around an Albunack discography.

Thursday 4 June 2015

SongKong 3.15 Released

SongKong 3.15 Released

Today we release a new version of SongKong

Firstly this includes modifications required to work with cover art newly added to Discogs in the last two months, this is required due to a change in how Discogs provides their cover art data.

Then we have fixed a problem matching song title and track total when matching multi-disc Discogs releases.

We recommend you update to this latest version of SongKong and then run Fix Songs over your collection with  the For Songs Already Matched to MusicBrainz releases option set to Update Metadata and Filename Only. This will fix any data that may have been incorrectly added in earlier releases and will also updated your previously matched songs the very latest data added to MusicBrainz and Discogs.

New versions of Jaikoz and Jthink Music Server

New version of JThink Music Server 

Yesterday we released a new version of the JThink Music Server - this is what powers Jaikoz, SongKong and Albunack . This latest release fixes an issue with incorrect values for the Sort Artist field. It also add supports for the latest Discogs cover art, required because the way cover art has been provided by Discogs for releases added over the last couple of months has changed.

New version of Jaikoz Music Tagger 8.2.3

Today we release a new version of Jaikoz.

Firstly this includes modifications required to work with cover art added to Discogs in the last two months.

Then we have fixed two problems related to song titles and track total when matching multi-disc Discogs releases.

Then we have fixed a regression whereby the Only Update Year if Earlier option for the Year field was ignored so this field could be overwritten with a later date.

We recommend you update to this latest version of Jaikoz and then run Update Metadata from MusicBrainz and Update Metadata from Discogs to fix any data that may have been incorrectly added in earlier releases and to benefit from the very latest data added to MusicBrainz and Discogs.

Wednesday 29 April 2015

Jaikoz 8.2.2 Available

A new release of  Jaikoz with a couple of bug fixes.

Delete Duplicate key check should be case insensitive

Delete Duplicate key check should be case insensitive to protect against tools that write identifiers with uppercase letters.

Only Allow Match if All Songs In Grouping Match to One Album should be true

Only Allow Match if All Songs In Grouping Match to One Album is defaulting to false on new install it should default to true otherwise existing songs grouped by album could be split if Jaikoz can match the songs but not all to the same album.

Tuesday 28 April 2015

Albunack, bringing Discogs and MusicBrainz together.

MusicBrainz is the defacto standard for Music, MusicBrainz Ids are used by many of the major players in online Music services such as Google the BBC and Spotify, and the MusicBrainz schema is a thing of beauty. But it has always been difficult getting the latest releases into MusicBrainz because there are no automated feeds from record companies and it mainly relies on the hard work of the many contributors.

Discogs is another online database, its not as well designed as MusicBrainz and its codebase is not open, but it has more artists and more releases and does make its database available monthly under a public domain license. Discogs has a vibrant marketplace, but to sell a record it has to be in the database, this is a good reason for users to contribute releases, and because buyers need to know exactly what they are purchasing sellers need to enter the details accurately.

For years I have wanted to something to make it easier for editors to get data into MusicBrainz from Discogs in some form or other but never seemed to have the time, but over the last month I have been working on a solution and now I have beta available as: http://albunack.net

The idea is you look up an artist and it shows you a combined MusicBrainz + Discogs discography, showing releasegroups/release and tracks on a single page.

Here is an example for the Pale Saints, a greatly under appreciated UK band from the early 90's

This makes it easier to see gaps in the MusicBrainz which could be filled by data from Discogs, and makes it easier to add that data:
  • It shows any existing links between MusicBrainz and Discogs matches. 
  • It also matches up Musicbrainz releases without a Discogs link to potential Discogs releases and lists these matches together with a Link button to seed a MusicBrainz Edit release. 
  • It provides an Import button to seed a MusicBrainz Add Release from other Discogs releases not linked to Musicbrainz  
I have been testing it myself over the last few weeks and it is so much quicker and so much safer  then previous ways I have used of adding data. Ive also found it is very good at showing when there is incorrect data in either MusicBrainz or Discogs.

You can also use it to check automated tagging done by SongKong or Jaikoz since they use the same underlying database.

Currently it only shows releases where the artist is the only album artist credit (i.e we don't list collaborations, nor Various Artist releases) Of course, the user still has to make decisions about the data and check the data before submitting anything to MusicBrainz, and everything still goes through the edit system. You can use the bug tracker for raising any issues.
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