hcd 2010 - NIPS Workshop on Modeling Human Communication Dynamics

NIPS Workshop on Modeling Human Communication Dynamics
Friday, December 10th, 2010
Whistler, British Columbia, Canada
http://projects.ict.usc.edu/hcd2010/


Description

Face-to-face communication is a highly interactive process in which
the participants mutually exchange and interpret verbal and nonverbal
messages. Both the interpersonal dynamics and the dynamic
interactions
among an individual's perceptual, cognitive, and motor processes are
swift and complex. How people accomplish these feats of coordination
is a question of great scientific interest. Models of human
communication
dynamics also have potential practical value, for applications
including
the understanding of communication problems such as autism
and the creation of socially aware robots able to recognize,
predict, and analyze verbal and nonverbal behaviors in real-time
interaction with humans.

Modeling human communicative dynamics brings exciting new problems
and challenges to the NIPS community. The first goal of this
workshop
is to raise awareness in the machine learning community of these
problems,
including some applications needs, the special properties of these
input streams, and the modeling challenges. The second goal is to
exchange
information about methods, techniques, and algorithms suitable for
modeling human communication dynamics. After the workshop, depending
on interest, we may arrange to publish full-paper versions of
selected
submissions, possibly as a volume in the JMLR Workshop and Conference
papers series.

Topics

We invite submissions of short high-quality papers describing
research
on Human Communication Dynamics and related topics. Suitable themes
include, but are not limited to:

* Modeling methods robust to semi-synchronized streams (gestural,

lexical, prosodic, etc.)
* Learning methods robust to the highly variable response lags seen
in

human interaction
* Coupled models for the explicit simultaneous modeling of more than

one participant
* Ways to combine symbolic (lexical) and non-symbolic information
* Learning of models that are valuable for both behavior recognition

and behavior synthesis
* Algorithms robust to training data with incomplete or noisy labels
* Feature engineering
* Online learning and adaptation
* Models of moment-by-moment human interaction that can also work for

longer time scales
* Failures and problems observed when applying existing methods
* Insights from experimental or other studies of human communication
* Concrete applications

Invited speakers

* Janet Bavelas (University of Victoria)

* Marian Stewart Bartlett (University of California, San Diego)

* Jeff Bilmes (University of Washington)

* Dan Bohus (Microsoft Research)

* Justine Cassell (Carnegie Mellon University)

* Noah D. Goodman (Stanford University)

Submission guidelines

Submissions should be written as extended abstracts, no longer than
4 pages in the NIPS latex style. NIPS style files and formatting
instructions can be found at http://nips.cc/PaperInformation/StyleFiles
(we will not enforce the double blind rule). Work that was recently
published or presented elsewhere is allowed, provided that the
extended
abstract mentions this explicitly; work earlier presented at non-ML
venues is especially encouraged. Please send your submission by email
to hcd2010-AT-ict.usc.edu by October 18th, 2010 at 11:59pm PDT.

Important dates

Submission deadline (extended): October 18th, 2010, 11:59pm PDT
Notification of acceptance: November 7th, 2010
Workshop: December 10th, 2010

Organizers

Louis-Philippe Morency, University of Southern California, USA
Daniel Gatica-Perez, Idiap Research Institute, Switzerland
Nigel Ward, University of Texas, El Paso, USA

Sponsored by the PASCAL 2 European Network of Excellence on
Pattern Analysis, Statistical Modeling, and Computational Learning