mypyspace status update

So MyPySpace has been getting a facelift.  Kurt with some input from users (we apparently have users!  Who knew.) has been refactoring the rdf translators and fine tuning the myspace ontology as well.  Most (all?) of these changes are also being reflected into the live service.  While all of this has been going on, I've refactored the page scraping, crawling and downloading into a much more sensible class architecture from it former stream of consciousness implementation (I believe the polite description is 'research code').  It still has quite a ways to go (alpha!) but it's starting to resemble an actual library.  If you want to play with my refactored bits you can check them out like this:

> svn co https://mypyspace.svn.sourceforge.net/svnroot/mypyspace/myspaceCrawler/trunk/ myspaceCrawler

then you can do nifty things like the following (inside your favorite python interpreter or script, I'm using ipython here):

In [1]: import mpsUser

In [2]: gearmonkey = mpsUser.mpsUser('http://www.myspace.com/gearmonkey')

You simply give the class a valid myspace user url to initialize it (this is my artist page.  If you want to play with this, don't feel the need to listen to my music...)

In [3]: gearmonkey.isArtist

Out[3]: True

In [4]: gearmonkey.downloadTracks('~/Music/mpsUsertest/gearmonkey/')

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/gearmonkey/1_Cheeky.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/gearmonkey/2_TrainTune.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/gearmonkey/3_Give Way.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/gearmonkey/4_En La Selva Mvt II GMO vip.mp3; creating tag from scratch

Out[4]: (4, 4)

Then you can find out if your user is an artist by checking the boolean isArtist.  If it's an Artist, you can download their songs.  That return value is a tuple of (songs successfully downloaded, downloads attempted). 

In [5]: gearmonkey.songs[0].title

Out[5]: u'Cheeky'

As part of the download process, each song is an instance of the class mpsSong (more on that class in a bit).

You can use the mpsUser class to crawl the artist network like this:

In [6]: artistFriends = gearmonkey.findArtistTopFriends()

In [7]: artistFriends

Out[7]: 

[mpsUser.mpsUser instance at 0x1a3a7b0,

 mpsUser.mpsUser instance at 0x1c5d788,

 mpsUser.mpsUser instance at 0x1a3ad50,

 mpsUser.mpsUser instance at 0x1a3a968,

 mpsUser.mpsUser instance at 0x1c7fc88]

In [8]: artistFriends[0].artist

Out[8]: u'Mike'

In [9]: for entry in artistFriends:

   ...:     print entry.artist

   ...:    

Mike

Otto Von Schirach

GEIN

The Dead Hookers' Bridge Club

EVOL

In [10]: artistFriends[2].downloadTracks('~/Music/mpsUsertest/GEIN/')

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/GEIN/1_Life Of Sin GEIN edit.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/GEIN/2_Deadly Algorhythm GEIN Remix.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/GEIN/3_GEIN KJ Sawka Break the Enemy.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/GEIN/4_GEIN  Warden.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/GEIN/5_GEIN vsThe ChosenAbomination.mp3; creating tag from scratch

INFO:root:No ID3 header found for /Users/bfields/Music/mpsUsertest/GEIN/6_GEIN  Hell Audio rmx.mp3; creating tag from scratch

Out[10]: (6, 6)

In [11]: artistFriends[2].topFriends

Out[11]: 

[u'11187934',

 u'2123795',

 u'2177245',

 u'706581',

 u'20492111',

 u'66601290',

 u'5017015',

 u'207669100',

 u'52365642',

 u'2186134',

 u'3378431',

 u'55609497',

 u'30244',

 u'26629700',

 u'80613962',

 u'74772580',

 u'28841051',

 u'317327']

In [12]: geinArtistFriends = artistFriends[2].findArtistTopFriends()

In [13]: geinArtistFriends

Out[13]: 

[mpsUser.mpsUser instance at 0x1d83a30,

 mpsUser.mpsUser instance at 0x1d95710,

 mpsUser.mpsUser instance at 0x1d99198,

 mpsUser.mpsUser instance at 0x1d95be8,

 mpsUser.mpsUser instance at 0x1d956c0,

 mpsUser.mpsUser instance at 0x1e6fa80,

 mpsUser.mpsUser instance at 0x1e81b98,

 mpsUser.mpsUser instance at 0x1da7080,

 mpsUser.mpsUser instance at 0x1e81b70,

 mpsUser.mpsUser instance at 0x1f2dee0]

In [14]: for friend in geinArtistFriends:

   ....:     print friend.artist

   ....:    

EVOL

GUERILLA®

THE GUN

Habit Recordings

Mumblz / Delusional

Tech Itch

Lost Soul Recordings

None

Donny

NECRO THE SEXORCIST SPECIAL EDITION CD/DVD SOON!!!

and so on and so forth.  Once you've initialized the songs for an artist you can use the mpsSong class structure to find things out about the songs as well:

In [15]: gearmonkey.songs

Out[16]: 

[mpsUser.mpsSong instance at 0x1a155d0,

 mpsUser.mpsSong instance at 0x1a2ff08,

 mpsUser.mpsSong instance at 0x1a338f0,

 mpsUser.mpsSong instance at 0x1a338c8]

In [17]: for song in gearmonkey.songs:

   ....:     print song.title + " by " + song.parent.artist + " has been played " + song.playcount + " times." 

   ....:    

Cheeky by G_M_O has been played 117 times.

TrainTune by G_M_O has been played 168 times.

Give Way by G_M_O has been played 88 times.

En La Selva Mvt II GMO vip by G_M_O has been played 9 times.

In [18]: 

There are also some simple hooks to call fftExtract on the songs of an artist but I'll save those bits for another post.   One quick note, I don't believe we've fixed the bug that prevents song downloads in the US (and maybe Canada), but the url requests have been changed slightly so if anyone tries it over there let me know.  All the scraping should be fine in the States and everything should work everywhere else.  Also, you need the mutagen ID3 tag library installed prior to using this.  

If any readers do give this a try let me know if you have any thoughts (especially interface related) down below.

introductory thoughts on a playlist generation task in MIREX 2009

I'm currently knee deep in ISMIR activities, of which I will do a more thorough write up when everything has finished. Now, however, I think it will be useful to briefly discuss a MIREX 2009 task I'll be pushing for, that of automatic playlist generation. I think it will be very useful to formalize as much of this task as possible as soon as possible, in effort to encourage participation and avoid the nearly standardized MIREX august rush.

With that in mind, here some the basic starting questions followed by my [brief and biased] thinking on them:

1. What is a playlist?
   
   

   From wikipedia:

   In its most general form, a playlist is simply a list of songs. The term has several specialized meanings in the realms of radio broadcasting and personal computers.
   The term originally came about in the early days of top 40 radio formats when stations would devise (and, eventually, publish) a limited list of songs to be played. ...
   As music storage and playback using personal computers became common, the term playlist was adopted by various media player software programs intended to organize and control music on a PC such as Nexus from NexTune. ...
   Some websites allow categorization, editing, and listening of playlists online, such as Project Playlist, Plurn, imeem and Webjay. ...
   

   
   This is a sensible starting place from a broad definitional stand, especially when we acknowledge that the exact MIREX will obviously be a subset within the idea of a playlist (more on that later...)
   




2. How do we quantitatively evaluate an automatically generated playlist?

   Upon a brief reflection this is clearly the sticky bit. As such this question is being posed prior to any sort attempt to specify an exact task. Functionally speaking, if the evaluation is properly specified the ask description will practically fall out of it.
   There seem to be a few approach to this, though many tend to revolve around an idea of mining some form of ground truth out of crowd wisdom (here and here for instance)




3. And of course, what exactly should the task be?

   Again, this is of course all very draftish, but my prime thought on this is to have a highly specific task of one (or all) of the following forms: query with song A B C algorithm generates song D (and perhaps song E, where order matters), the simple deviation of that form given A B E, generate C D. The other possibility is something alog the lines of give a query song and provide the next song that should occur in the list.

So anyway, those are my initial thoughts on this potential task for next years MIREX. Please comment if you have thoughts...

A brave new world

This morning as I 'opened' my NY Times, what do I discover but a review of the new google browser, not in the tech section or the style section, but as an editorial piece. Who would have thought that a New York Times editorial would read like it was on Ars Technica. Clearly these are interesting times.

in between an ICMC and an ISMIR

So I'm gathering my thoughts on ICMC (I presented this poster) while simultaneously prepping for my poster/presentation for ISMIR (paper).

ICMC was very interesting. Kurt has a nice summary of a few of the notable papers. I did actually go to Bob Strum's presentation on Friday and there tech has some amazing potential as well as a rather slick interface (especially for research software...). Beyond this though, I spent a good portion of the paper sessions attending the discussions on aesthetic and philosophical considerations, in part because I have approximately no formal background in that sort of thing and as I'm setting out to make playlists (and mix them) in a way that's pleasing (or at least interesting). So I heard a very interesting talk by Gary Kendall presenting an attempt at an event based descriptor schema for Electro-Acoustic music (can't find the paper online...). While I must admit that the details of the schema's application to Electro-Acoustic music left something to be desired, I found the general constructs of attempting to define event based descriptors of things like expectation and energy expended to be very intriguing.

I have some video from the mobile phone orchestra performance, that I'll be posting a bit later, providing it's worth looking at.

Back to prepping for ISMIR.

A mashed08 debrief

So over the weekend I attended the hackfest that BBC puts, Mashed08. It was a 2 day marathon sort of hackfest where BBC and other sponsors (Yahoo was pushing their new locator techFire Eagle for instance) walked you through some newish API or otherwise accessible tech then you had 24 hours to make something rad. Each sponsor gave out prizes in the end for the hacks they judged to be the best at using their bits.

Yves, Kurt and I set out to make something rad as well. The basic idea was to recommend BBC radio brands (shows) based on the music in your personal collection. We (mostly, kindof) made this work.

The idea is that you generate rdf describing your audio collection (or a subset) using gnat, which is a piece of the music ontology tools. This rdf file contains the MusicBrainz IDs for your tracks which can then be cross referenced against the available playlists for BBC radio shows in order to find the best matches.

The biggest problem we encountered (which seems obvious now but didn't when we started) is that a collection of non-trivial size generates way too many results to be useful and we didn't implement any sort of ranking scheme to present the results in a way that is useful, though this could easily be done and maybe one of us will add this at some point...

Also, there was a tech crunch write of the weekend that shortlisted our project, which is neat. (The Guardian has a more comprehensive article as well). Finally, for posterity:



more pictures

Needs something to do tomorrow?

I'm going to be DJing at this event at the Dana Centre in London tomorrow. The playlist for my DJ set has been automatically generated using both social network information (from Myspace) and acoustic similarity measures. If you're intrigued, come to the event. if you can't make the event, the algorithm will be presented in an ISMIR paper this year, so you'll be able to see a bit of it there (if you're the ISMIR attending type. You know who you are...)

Greatest example of a need for data compression...

From the duke.
I believe the entropy of that set is actually zero, since both artists are functionally the same, so with an nice compression algorithm with the same two hour fixed transfer time, the transfer rate goes to infinity.

ha!