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CSLI Calendar, Wednesday, 30 July 2003, vol. 18:44
CSLI CALENDAR OF PUBLIC EVENTS
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30 July 2003 Stanford Vol. 18, No. 44
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A weekly publication of the
Center for the Study of Language and Information (CSLI)
Stanford University, Ventura Hall, Stanford, CA 94305-4115
http://www-csli.stanford.edu/
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ACTIVITIES FROM 30 JULY 2003 TO 8 AUGUST 2003
THURSDAY, 31 JULY 2003
11:00am Music 319: CCRMA Hearing Seminar
CCRMA Library, The Knoll
"Semantic Music Space, and a Music Similarity Browser"
Adam Berenzweig
Columbia University
http://mambo.ucsc.edu/psl/ccrmas/ccrmas.html
Abstract below
4:00pm PARC Forum
George Pake Auditorium at PARC
"Bridging the Global Digital Divide with Recycled Computers"
Richard Gingras
http://www.parc.com/forum/
Abstract below
7:00pm MS&E237: Progress in Worldwide Telecommunications
Skilling 193
"Towards Ubiquitous Networked Society"
Shingo Ohmori
Executive Director, Strategic Planning Division
Communications Research Laboratory, Japan
RSVP to ivenak@stanford.edu (RSVP required)
THURSDAY, 7 AUGUST 2003
4:00pm PARC Forum
George Pake Auditorium at PARC
"Everything you didn't know you wanted:
The Forrester Electronic Toy Show"
Dan Rasmus and Rob Enderle
Forrester Research, Giga Information Group
http://www.parc.com/forum/
Abstract below
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A+, B-, AB+, and AB-. For an appointment:
http://bloodcenter.stanford.edu/ or call 650-723-7831. It only takes
an hour of your time.
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MUSIC 319: CCRMA HEARING SEMINAR
on Thursday, 31 July 2003, 11:00am
CCRMA Library, The Knoll
http://mambo.ucsc.edu/psl/ccrmas/ccrmas.html
What makes two musical signals similar? Adam Berenzweig from Columbia
will be leading the discussion at this week's CCRMA Hearing Seminar.
How do you decide if two pieces of music are similar? Genre is one
aspect of this problem, and people identify musical genre in a few
notes. How do we make these decisions, and what does your musical
space look like?
Adam's solution is to build a model of a musical piece--an anchor
model--and then measure the likelihood that another piece of music
fits that model. A model that represents songs by John Denver will
not predict music from Green Day. Combine a number of anchor models
and you get a representation of musical space. Does this work? How
do we evaluate this? Come to CCRMA to hear more.
Bring your ears and your ideas about similarity to CCRMA
-- Malcolm
"Semantic Music Space, and a Music Similarity Browser"
Adam Berenzweig
Columbia
I will talk about a method of mapping music into a semantic space that
can be used for similarity measurement, classification, and music
information retrieval. The value along each dimension of this "anchor
space" is computed as the output from a classifier which is trained to
measure a particular semantic feature, for example music genre. In
anchor space, distributions that represent objects such as artists or
songs are modeled with Gaussian Mixture Models, and these
distributions can be compared using an approximation to the
Kullback-Leibler divergence. Evaluation is one of the most
problematic aspects of this research, and several evaluation methods
using various sources of human similarity judgments are explored. An
artist classification experiment using the models will also be
presented. Finally, a music similarity browsing application will be
demonstrated ( http://www.playola.org/ ), with a novel interface that
makes use of the fact that anchor space dimensions are meaningful to
users.
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PARC FORUM
on Thursday, 31 July 2003, 4:00pm - 5:00pm
George Pake Auditorium, PARC
http://www.parc.com/forum/
"Bridging the Global Digital Divide with Recycled Computers"
Richard Gingras
For the last four years the World Computer Exchange has been building
an organization to place used computers in schools in under-developed
countries. The approach of the Exchange both aids in the education of
youth in developing countries while extending the useful life of
discarded PC's that would otherwise be added to landfills. Richard
Gingras, a Silicon Valley veteran and active WCE board member, will
discuss the efforts and challenges faced by the Exchange in addressing
this complex but beneficial mission.
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PARC FORUM
on Thursday, 7 August 2003, 4:00pm - 5:00pm
George Pake Auditorium, PARC
http://www.parc.com/forum/
"Everything you didn't know you wanted:
The Forrester Electronic Toy Show"
Dan Rasmus and Rob Enderle
Forrester Research, Giga Information Group
We will walk you through products you can put on your short list for
Christmas or think about using to impress that special relative or
friend. In this session, our key analysts rapidly go through a long
list of products that can improve, excite, or complicate our lives. We
will cover the good, the bad, and the incredibly ugly and do it all
with our tongue solidly stuck in our cheeks. As much entertainment as
content, this is one session you will remember into the new year.
About the Speakers: Daniel W. Rasmus covers knowledge management (KM)
and collaboration for Giga Information Group with more than 20 years
of IT experience. Dan has been involved in client interaction and
research for many companies in North America and Europe. He has worked
with a large number of industry leaders and emerging companies,
including Lotus, Microsoft, Intel, AIG, US Postal Service, BAE. Dan is
editorial advisor to PC AI Magazine and the author of 190 trade
journal articles and three books, including Rethinking Smart Objects
and Leveraging Knowledge (U of Cambridge Press). Dan attended the UC
Santa Cruz, and received a certificate in intelligent systems
engineering from the UC Irvine. He has also been a guest lecturer at
the UC Irvine and Stanford University.
Rob Enderle is an analyst providing IT advice for the desktop. His
current client activities include helping companies anticipate future
changes in personal computing technology. Robs client and research
activities have covered the PC space from vendors like IBM, Dell and
Compaq, to technology companies like Intel, Creative Labs and Matrox,
and has included software companies like Symantec and Microsoft. In
2002, Technology Marketing named Rob as one of the 20 most influential
industry analysts. Rob earned a marketing degree from Orange Coast
College, a B.S. in business and an M.B.A. with an emphasis on market
research, both from the CalState Long Beach, and a C.M.A. Certificate
from Pace University.
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