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* Apologies for cross postings *<br>
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<a moz-do-not-send="true"
href="http://ralli.ofai.at/workshop.html">Workshop on Cognitive
Architectures for Situated Multimodal Human Robot Language
Interaction (ICMI 2018)</a><br>
October 16th, in Boulder, Colorado<br>
Extended paper submission deadline: July 31, 2018<br>
Invited talks: John Laird, Chen Yu<br>
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Overview<br>
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The workshop will take place in conjunction with the 20th ACM
International Conference on Multimodal Interaction (ICMI 2018) in
Boulder, Colorado on the 16th of October.<br>
In many application fields of human robot interaction, robots need
to adapt to changing contexts and thus be able to learn tasks from
non-expert humans through verbal and non-verbal interaction.
Inspired by human cognition, we are interested in various aspects
of learning, including multimodal representations, mechanisms for
the acquisition of concepts (words, objects, actions), memory
structures etc., up to full models of socially guided, situated,
multimodal language interaction. These models can then be used to
test theories of human situated multimodal interaction, as well as
to inform computational models in this area of research.<br>
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Call for Papers<br>
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The workshop aims at bringing together linguists, computer
scientists, cognitive scientists, and psychologists with a
particular focus on embodied models of situated natural language
interaction. Workshop submissions should answer at least one of
the following questions:<br>
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* Which kind of data is adequate to develop socially guided models
of language acquisition, e.g. multimodal interaction data, audio,
video, motion tracking, eye tracking, force data (individual or
joint object manipulation)?<br>
* How should empirical data be collected and preprocessed in order
to develop cognitively inspired models of language acquisition,
e.g. should either HH or HR data be collected?<br>
* Which mechanisms are needed by the artificial system to deal
with the multimodal complexity of human interaction? How can the
information transmitted via different modalities be combined at a
higher level of abstraction?<br>
* Models of language learning through multimodal interaction: How
should semantic representations or mechanisms for language
acquisition look like to allow an extension through multi-modal
interaction?<br>
* Based on the above representations, which machine learning
approaches are best suited to handle the multimodal, time-varying
and possibly high dimensional data? How can the system learn
incrementally in an open-ended fashion?<br>
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Invited Speakers<br>
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Keynotes will be given by John Laird, Professor at the faculty of
the Computer Science and Engineering Division of the Electrical
Engineering and Computer Science Department of the University of
Michigan, and Chen Yu, Professor at the Computational Cognition
and Learning Lab at Indiana University.<br>
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Important Dates<br>
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Extended paper submission deadline: July 31, 2018<br>
Notification of acceptance: August 15, 2018<br>
Final version: August 24, 2018<br>
Workshop: October 16, 2018<br>
Submission Instructions<br>
Articles should be 4-6 pages, formatted using the ACM template of
the ICMI conference. For each accepted contribution, at least one
of the authors is required to attend the workshop.<br>
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Organizers<br>
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Stephanie Gross, Austrian Research Institute for Artificial
Intelligence, Vienna, Austria<br>
Brigitte Krenn, Austrian Research Institute for Artificial
Intelligence, Vienna, Austria<br>
Matthias Scheutz, Department of Computer Science at Tufts
University, Massachusetts, USA<br>
Matthias Hirschmanner, Automation and Control Institute at Vienna
University of Technology, Vienna, Austria<br>
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