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DejaVU Online
-- Musical Feature Detection in ACOI
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ACOI
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References
There is a wealth of powerful search engines on the Web.
Technically, search engines rely either on classification schemes
(as for example Yahoo)
or content-based (keyword) indexing
(as for example Excite or AltaVista).
Searching on the Web, nowadays, is moderately effective
when text-based documents are considered.
For multimedia objects (such as images or music)
existing search facilities are far less effective,
simply because indexing on category or keywords can
not be done automatically.
We will first give some examples of search based on keywords
and categories, then some examples of content-based search and
finally we will discuss a more exhaustive list of
musical databases and search facilities on the Web.
Keywords and categories
For musical material, in particular MIDI,
there are a number of sites that offer search over
a body of collected works.
One example is the Aria Database [Aria], that allows
to search for an aria part of an opera based on title,
category and even voice part.
Another example is the MIDI Farm [Farm],
which provides many MIDI-related resources, and
also allows for searching for MIDI material
by filename, author, artist and ratings.
A category can be selected to limit the search.
The MIDI Farm employs voting to achieve collaborative
filtering on the results for a query.
Search indexes for sites based on categories and keywords
are usually created by hand, sometimes
erreonously. For example, when searching for a Twinkle fragment,
Bach's variations for Twinkle were found,
whereas to the best of our knowledge
there exist only Twinkle variations by Mozart [Mozart].
The Digital Tradition Folksong Database [Folk] provides
in addition a powerful lyrics (free text) search facility based
on the AskSam search engine [AskSam].
An alternative way of searching is to employ a meta-search engine.
Meta-search engines assist the user in formulating an appropriate
query, while leaving the actual search to (possibly multiple)
search engines.
Searching for musical content is generally restricted to the lyrics,
but see below (and section [Match]).
Content-based search
Although content-based search for images and sound have
been a topic of interest for over a decade [MM],
few results have been made available to the public.
As an example, the MuscleFish Datablade for Informix [Muscle],
allows for obtaining information from audio based on a content
analysis of the audio object.
As far as content-based musical search facilities for the Web
are concerned, we have for example,
the Meldex system of the New Zealand Digital Library
initiative, an experimental system that allows for searching tunes
in a folksong database with approximately 1000 records [Meldex].
Querying facilities for Meldex include queries
based on transcriptions from audio input, that is humming a tune!
We will discuss the approach taken for the Meldex system in more
detail in section [Match],
to assess its viability for retrieving musical fragments
in a large database.
Music databases
In addition to the sites previously mentioned,
there exist several databases with musical information on the Web.
We observe that these databases do not rely on DBMS technology
at all.
This obviously leads to a plethora of file formats and
re-invention of typical DBMS facilities.
Without aiming for completeness, we have for example
the MIDI Universe [Robot],
which offers over a million MIDI file references,
indexed primarily by composer and file length.
It moreover keeps relevant statistics on popular tunes,
as well as a hot set of MIDI tunes. It further offers
access to a list of related smaller MIDI databases.
Another example is the aforementioned Meldex system [MeldexDB],
that offers a large collection of tunes (more than 100.000),
of which a part is accessible by humming-based retrieval.
In addition text-based search is possible against
file names, song titles, track names and (where available) lyrics.
The Classical MIDI Archive [Classic] is an example of a database
allowing text-based search on titles only.
Results are annotated with an indication of "goodness"
and recency.
The Classical Themefinder Database [Themes] allows extensive support
for retrieval based on (optional) indications
of meter, pitch, pitch-class, interval, semi-tone interval
and melodic contour, within a fixed collection of works
arranged according to composer and category.
The index is clearly created and maintained manually.
The resulting work is delivered in the MuseData format,
which is a rich (research-based) file format from
which MIDI files can be generated [Beyond].
A site which collects librarian information concerning
music resources is the International Inventory of
Music Resources (RISM) [RISM], which offers search facilities
over bibliographic records for music manuscripts, librettos
and secondary sources for music
written after c.a. 1600.
It also allows to search for libraries related to the RISM site.
Tune recognition is apparently offered by the Tune Server [Tunes].
The user may search by offering a WAV file with
a fragment of the melody.
However, the actual matching occurs against a melodic
outline, that is indications of rising or falling in pitch.
The database contains approx. 15.000 records with such pitch contours, of which one third are popular tunes and the rest classical themes.
The output is a ranked list of titles about which the user is asked to give
feedback.
Discussion
There is great divergence in the scope and aims of music
databases on the Web.
Some, such as the RISM database [RISM], are the result
of musicological investigations,
whereas others, such as the MIDI Farm [Farm],
are meant to serve an audience looking for popular tunes.
With regard to the actual search facilities offered,
we observe that, with the exception of Meldex [Meldex]
and and the Tune Server [Tunes],
the query facilities are usually text-based,
although for example the Classical Themefinder [Themes]
allows for encoding melodic contour in a text-based fashion.
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