Re: [MMSEM-UC] review of Music Use Case

Hi guys, tomorrow thruddsay we have the kick off meeting of the
Discovery project (the one who's hopefulyl paying for us to be in the XG
:-) ) so we wont be able to attend. Regrets from me and christian then

at ISWC me and oscar had a change to talk and to confirm that it is a
difficult issue what is a good use case and what is not. Many things can
be done without semantic web technolgoies.. for others it seems obvious
to use them to the point that the UC is simply "write this in rdf ,
write that in rdf hurray you're compatible" :-)

during a discussion also with jeff pan i raised the idea that probably
keeping an up to date - reference  list and comparison of projects,
vucabolaries and tool might be the best a w3c group can do to foster
actual use of such tecnologies.
This doesnt meant this is the only thing that can be done, it is just
probably more important than "jsut a list" ..
Coming back nex week but will be checking the mail and read the minutes
ciao ciao! :-)



Raphaël Troncy wrote:
> Dear XG members,
>
> Oscar Celma, future new member of the XG from UFP has written very
> interesting thoughts that I reproduce below about the Music Use Case.
> You can see also his wiki web page:
> http://www.w3.org/2005/Incubator/mmsem/wiki/OscarCelma
> Best regards.
>
>     Raphaël
>
> ---------------------
>
> Now, regarding the Music Use Case. I've been thinking about it... My
> main concern is that it tries to cover a wide range of topics with
> regard to Music Information Retrieval (MIR),and Semweb fields. For
> instance, it includes:
> - audio fingerprinting
> - metadata aggregation
> - playlist generation
> - ...
>
> I think that a feasible music use-case should focus on one, or maybe a
> couple of ideas. Else, it is too much!
> Moreover, there is a lot of ongoing work in most of these fields: I'm
> thinking on MusicDNS(+MusicBrainz) audio identification service,
> Last.fm, Pandora (and a looong etcetera) for playlist generation, etc.
>
> Therefore, the use case could be "misunderstood", in the sense that
> *people* could not get the point of adding explicit semantics to the
> ideas presented in the use case... That said, I think it would be
> fantastic to cope with the whole music  use case ideas, but I think it
> is too big now!
>
> So, I rush a couple of ideas here:
> * The first proposal is to exploit the propagation of (semantic) music
> annotations.
>
> This idea includes the following tasks:
> 1- Extract mid-level features from the audio. (i.e: beats per minute
> (BPM), tonality (Key and mode), timbre characteristics, etc.)
> 2- User interaction with her music collection: Once the audio files have
> been analysed, the user can tag some songs according to his criterion.
> The user could create concepts such as Mood (with the following
> categories: happy, sad, mysterious, etc.), and
> attach some examples (i.e songs) for each class.
> 3- The system could propose a set of tags (a category value for a
> concept) for newly incoming songs, based on audio similarity metrics.
> That is, when a new song is added to the music collection, and is
> analyzed, then the system can get the category values from the most
> similar songs, and propagate these annotations to the new song.
> 4- (Rellevance feedback step). The user can accept or reject the
> tags'proposals made by the system.
>
> This process show how to *easily* annotate music collections by
> expanding the annotations of music titles.Think of Pandora, that now
> does all the music description manually (more than 400 attributes!).
> This use case would help them in speeding up the process of annotating
> big collections.
>
> That's a rough idea, so instead of tags (linked somehow with the Wordnet
> RDF/OWL representation [8]?), could be normalized by a predefined
> ontology. Finally, this use case, is clearly related with the "Tagging
> Use Case" proposal.
>
> * The second idea is to add semantics to a Podcast session.
> Nowadays, there is no metadata about a podcast session. The most useful
> thing one can found is some sort of HTML tables into the RSS feed entry,
> that include the songs and artists appearing on the podcast session.
> Then, a nice use-case will be to add explicit metadata that allows to
> explain contents of the session.
>
> More concrete, I'm thinking on:
> 1- Speech/Music recognition.
> Detect from the MP3 file the bits where a person is speaking, and the
> parts that there is music (there's a lot of work in this area, probably
> the best would be to use the state-of-the-art algorithm that solves this
> problem with higher accuracy).
> 2- Once we have detected which parts includes music, the next step is to
> create a temporal structural decomposition of the podcast session (we
> could use parts of the some MPEG-7/OWL ontology, MDS part, to describe
> it).
> E.g:
> 00:04:02 - 00:06:22  :: Arctic Monkeys - A certain romance
> 00:06:35 - 00:08:04  :: The Killers  - Somebody told me
> etc.
>
> The main drawback here is to detect the music (audio identification).
> So, one option is using the fingerprinting, and the other is to analyze
> the text from the RSS entry, and try to derive tha artists and songs
> (hmmm... not very nice, though!).
>
> 3- After this, the temporal decomposition could be embedded into the RSS
> (think of RSS 1.0 or the Atom/OWL proposal by Henry Story)
>
> 4- Finally, we would get a nice description of the podcast session.
> After that, a nice SPARQL query to retrieving podcasts that include
> songs from user's favourite artists would be the killer app! :-) Related
> with these use case, see, for instance the work done at DERI at [9].
>
> That's all for now!
> Oscar Celma.
>
> [8] http://www.w3.org/2001/sw/BestPractices/WNET/wn-conversion.html
> [9] http://sw.deri.org/2005/07/podcast/doc/podcast.pdf
>
> --
> Raphaël Troncy
> CWI (Centre for Mathematics and Computer Science),
> Kruislaan 413, 1098 SJ Amsterdam, The Netherlands
> e-mail: raphael.troncy@cwi.nl & raphael.troncy@gmail.com
> Tel: +31 (0)20 - 592 4093
> Fax: +31 (0)20 - 592 4312
> Web: http://www.cwi.nl/~troncy/
>
>
>
>