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"Chi-Chun (Jeremy) Lee" <[log in to unmask]>
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Chi-Chun (Jeremy) Lee
Wed, 11 Apr 2018 09:42:23 +0800
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*International Conference on Multimodal Interaction (ICMI) *
Boulder, Colorado, October 16-20th, 2018

*Call for Workshop Articles for six confirmed ICMI 2018 Workshops:*
- Multi-sensorial Approaches to Human-Food Interaction (MHFI):
- Group Interaction Frontiers in Technology (GIFT) (
- Modeling Cognitive Processes from Multimodal Data (MCPMD):
- Human-Habitat for Health (H3):
- Multimodal Analyses enabling Artificial Agents in Human-Machine
Interaction (MA3HMI):
- Cognitive Architectures for Situated Multimodal Human Robot Language

Overview and general info:

The 20th International Conference on Multimodal Interaction (ICMI 2018)
will be held in Boulder, Colorado. ICMI is the premier international forum
for multidisciplinary research on multimodal human-human and human-computer
interaction, interfaces, and system development. The conference focuses on
theoretical and empirical foundations, component technologies, and combined
multimodal processing techniques that define the field of multimodal
interaction analysis, interface design, and system development.

ICMI 2018 is pleased to announce that six workshops have been confirmed and
will run immediately prior to the main conference on October 16th, 2018.
Please consider submitting your latest work to these exciting emerging


*3rd International Workshop on Multi-sensorial Approaches to Human-Food
Interaction (MHFI 2018)*
There is a growing interest in the context of Human-Food Interaction to
capitalize on multisensory interactions in order to enhance our food- and
drink- related experiences. This, perhaps, should not come as a surprise,
given that flavour, for example, is the product of the integration of, at
least, gustatory and (retronasal) olfactory, and can be influenced by all
our senses. Variables such as food/drink colour, shape, texture, sound, and
so on can all influence our perception and enjoyment of our eating and
drinking experiences, something that new technologies can capitalize on in
order to “hack” food experiences.
In this 3rd workshop on Multi-Sensorial Approaches to Human-Food
Interaction, we again are calling for investigations and applications of
systems that create new, or enhance already existing, eating and drinking
experiences (‘hacking’ food experiences) in the context of Human-Food
Interaction. Moreover, we are interested in those works that are based on
the principles that govern the systematic connections that exist between
the senses. Human Food Interaction also involves the experiencing food
interactions digitally in remote locations. Therefore, we are also
interested in sensing and actuation interfaces, new communication mediums,
and persisting and retrieving technologies for human food interactions.
Enhancing social interactions to augment the eating experience is another
issue we would like to see addressed in this workshop.


Carlos Velasco
Anton Nijholt
Marianna Obrist
Katsunori Okajima
Charles Spence


*Group Interaction Frontiers in Technology (GIFT)*
The Group Interaction Frontiers in Technology (GIFT) workshop aims to bring
together researchers from diverse fields related to group interaction, team
dynamics, people analytics, multi-modal speech and language processing,
social psychology, and organizational behaviour. The workshop will provide
a unique opportunity to researchers to share their knowledge and gain
insights outside their respective fields and will hopefully lead to
inter-disciplinary networking and fruitful collaboration.


Hayley Hung
Joann Keyton
Catherine Lai
Nale Lehmann-Willenbrock
Gabriel Murray
Catherine Oertel


*Modeling Cognitive Processes from Multimodal Data (MCPMD)*
Multimodal signals allow us to gain insights about internal cognitive
processes of a person, for example: Speech and gesture analysis yield cues
about hesitations, knowledgeability, or alertness, eye tracking yields
information about a person's focus of attention, task, or cognitive state,
EEG yields information about a person's cognitive load or information
appraisal. Capturing cognitive processes is an important research tool to
understand human behavior as well as a crucial part of a user model to an
adaptive interactive system such as a robot or a tutoring system. As
cognitive processes are often multifaceted, a comprehensive model requires
the combination of multiple complementary signals.


Felix Putze, University of Bremen
Jutta Hild, Fraunhofer IOSB
Enkelejda Kasneci, University of Tübingen
Akane Sano, MIT Media Lab/Cornell University
Erin Solovey, Drexel University
Tanja Schultz, University of Bremen


*Human-Habitat for Health (H3): Human-habitat multimodal interaction for
promoting health and well-being in the Internet of Things era*
In the Internet of Things (IoT) era, digital human interaction with the
habitat environment can be perceived as the continuous interconnection and
exchange of cognitive, social, and affective signals between an individual
or a group, and any type of environment built for humans (e.g., home, work,
clinic). Through the integration of various interconnected devices (e.g.,
built-in microphones of home devices, acceleration, GPS, and physiological
sensors embedded in smartphones or wearable devices, proximity sensors
installed in smart objects), we can collect multimodal data including
speech, spoken content, physiological, psychophysiological, and
environmental signals, that enable the sensing of a person’s activity,
mood, emotions, preferences, and/or health state, and ultimately provide
appropriate feedback. Applications of these include artificial
conversational agents (e.g., Amazon Alexa, Google Home) that enable voice
powered human computer interaction to provide new information (e.g.,
nutritional food content, weather forecast) or conduct procedural tasks
(e.g., update daily food intake diary, book a flight), in-the-moment
automatic habitat adaptation systems that provide comfort and relaxation,
human health and well-being support systems that are able to track the
progress of a disease (e.g., depression tracking through linguistic and
acoustic markers), detect high-risk episodes (e.g., suicidal tendencies),
and ultimately provide feedback (e.g., guide individuals through a brief
intervention) or take appropriate action (e.g., call 911). Special focus
will be given on the technical considerations and challenges involved in
these tasks ranging from the nature of the acquired data (e.g., noise, lack
of structure, issues of multi-sensory integration) to the high variability
present in habitat environments (e.g., different lighting conditions, room
acoustic characteristics), and the inherent unpredictability and
multi-faceted nature of human behavior. The H3 workshop aims to bring
together experts from academia and industry spanning a set of
multi-disciplinary fields, including computer science, speech and spoken
language understanding, construction science, life-sciences, health
sciences, and psychology, to discuss their respective views of the problem
and identify synergistic and converging solutions.


Theodora Chaspari, Assistant Professor, Computer Science & Engineering,
Texas A&M University ([log in to unmask])
Angeliki Metallinou, Senior Speech Scientist, Amazon Alexa Machine Learning
([log in to unmask])
Leah Stein Duker, Assistant Professor of Research, Occupational Science and
Therapy, University of Southern California ([log in to unmask])
Amir Behzadan, Associate Professor, Construction Science, Texas A&M
University ([log in to unmask])


*Multimodal Analyses enabling Artificial Agents in Human-Machine
Interaction (MA3HMI)*
One of the aims in building multimodal user interfaces and combining them
with technical devices is to make the interaction between user and system
as natural as possible in a situation as natural as possible. The most
natural form of interaction can be considered how we interact with other
humans. Although technology is still far from being human-like, and systems
can reflect a wide range of technical solutions. They are often represented
as artificial agents to facilitate smooth interactions. While the analysis
of human-human communication has resulted in many insights, transferring
these to human-machine interactions remains challenging especially if
multiple possible interlocutors are present in a certain area. This
situation requires that multimodal inputs from the main speaker (e.g.,
speech, gaze, facial expressions) as well as possible co-speaker are
recorded and interpreted. This interpretation has to occur at both the
semantic and affective levels, including aspects such as the personality,
mood, or intentions of the user, anticipating the counterpart. These
processes have to be ideally performed in real-time in order for the system
to respond without delays, in a natural environment. Therefore, the MA3HMI
workshop aims at bringing together researchers working on the analysis of
multimodal data as a means to develop technical devices that can interact
with humans. In particular, artificial agents can be regarded in their
broadest sense, including virtual chat agents, empathic speech interfaces
and life-style coaches on a smart-phone. We focus on the environment and
situation an interaction is situated in extending the investigations on
real-time aspects of human-machine interaction. We address the synergy of
situation, context, and interaction history in the development and
evaluation of multimodal, real-time systems.


Ronald Böck - Otto von Guericke University Magdeburg, Germany
Francesca Bonin - IBM Research, Ireland
Nick Campbell - Trinity College Dublin, Ireland
Ronald Poppe - Utrecht University, The Netherlands


*Cognitive Architectures for Situated Multimodal Human Robot Language
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. In the Workshop on
Cognitive Architectures for Situated Multimodal Human Robot Language
Interaction, we focus on robot action and object learning from
multimodal-interaction with a human tutor. Inspired by human cognition, the
research interests of this workshop tackle different aspects of robot
learning, such as (i) the kind of data used to develop socially guided
models of language acquisition, (ii) the collection and preprocessing of
empirical data to develop cognitively inspired models of language
acquisition, (iii) the multimodal complexity of human interaction, (iv)
multimodal models of language learning, and (v) adequate machine learning
approaches to handle these high dimensional data. 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 and the challenges will be discussed under a
multidisciplinary perspective.


Stephanie Gross, Austrian Research Institute for Artificial Intelligence,
Vienna, Austria
Brigitte Krenn, Austrian Research Institute for Artificial Intelligence,
Vienna, Austria
Matthias Scheutz, Department of Computer Science at Tufts University,
Massachusetts, USA
Matthias Hirschmanner, Automation and Control Institute at Vienna
University of Technology, Vienna, Austria

Jeremy (李祈均)

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