Query: Methods, Models, and User Studies
by Walter B. Hewlett and Eleanor Selfridge-Field,
Published by Center for Computer Assisted
Research in the Humanities and The MIT
Press, Cambridge, MA, 2005
Reviewed by Joao Pedro Martins, Marcelo
Gimenes and Qijun Zhang
Future Music Lab, University of Plymouth,
This is the third book by Walter B. Hewlett
and Eleanor Selfridge-Field, both researchers
at the University of Stanford, with the
stamp of the same publisher. It introduces
a number of articles by researchers around
the world who are in the lead of music
information retrieval, one of the currently
most active fields in music technology.
An equivalent interest began to happen
not long ago with the overwhelming growth
in the availability of information through
the Internet. Search engines have been
created to enable the access to information
with advanced word query methods.
Music entails the same sort of challenge.
What if one is capable of singing or perfectly
whistling a piece of music but cant
recall its title or composer? Furthermore,
what if this individual remembers only
parts of the music? How should it be possible
to find out a specific tune among millions
of others in a growing database?
This is where Music Query: Methods,
Models, and User Studies comes to
provide several clues on how the above
tasks could be improved. The subject of
music query methods is not only confined
to web applications, though. They also
play an important role in musicology by
establishing links in the evolution of
musical styles, and also by enhancing
copyright protection mechanisms. The current
trend is to establish distance measures
that take into account cognitive processes,
in order to better capture human perception
The book starts with a chapter by Vlora
Arifi and her colleagues from the University
of Bonn, addressing the problem of synchronisation
of streams of musical information. Synchronisation
of different representation formats is
pointed as being a promising possibility
to enhance the performance of music retrieval
systems. The idea is to link the representations
of the same piece of music in a large
database with the help of a well-defined
The analysis of rhythmic structures with
machine learning techniques is the subject
of the next chapter. Tillman Weyde presents
his Integrated Segmentation and Similarity
Model, which uses fuzzy logic rules to
rate alternatives for rhythmic structures.
This model shows a great concern for the
inclusion of perceptual features when
defining the fuzzy rules.
Another major issue addressed by music
information retrieval systems is the special
role played by melody on the recognition
of songs and musical styles. Wei Chai,
in chapter three, uses folk songs from
different countries to illustrate how
music styles can be distinguished by statistical
features described by Hidden Markov Models.
Several string-matching methods are proposed
which combine both pitch and rhythm information.
It also shows the importance of designing
melodic representation according to different
In chapter four, Olivier Lartillot and
Emmanuel Saint-James describe a new approach
to musical-pattern discovery that consider
the musical discourse as complex flows
of smaller structures. Their proposal
was implemented with OMKanthus,
a library based on IRCAM1s Open Music,
modelling cognitive mechanisms characteristic
of music perception.
In the next chapter, Eleanor Selfridge-Field,
proposes a preliminary distance melodic
metric based on cognitive principles.
Distance assessments take into account
pitch and harmonic conformance in relation
to metrical and accentual information.
Chapter six, by Frans Wiering, Rainer
Typke and Remco C.Veltkamp, introduces
the approach to use weighted dots for
music-notation retrieval. Two transportation
distance measures are defined and compared.
According to the experiments with monophonic
incipits, this approach has achieved higher
performance, compared with similar researches.
In chapter eight, Daniel Muellensiefen
and Klaus Frieler propose a research paradigm
or optimal melodic similarity measure
from the comparison of the results taken
from a multitude of algorithms and from
experiments with human music experts.
Several techniques are considered, depending
on the intended task and data to be analysed.
Finally, in chapter seven, Micheline Lesaffre,
Dirk Moelants, and Marc Leman report psychological
experiments on query type preferences
of the population. The key issue of the
experiment was not to initially constrain
the choices of the subjects. All the steps
of the research are very well documented
and the results show that some widely
used methods, like query-by-humming,
received a lower share of preference.
This book is not only designed for those
interested in music information retrieval
systems. Anyone who intends to carry out
research on music technology will certainly
benefit from its reading.