Brunel University researchers aiming to improve the user
experience are investigating computer systems that recognise and
respond to emotion
Imagine if a computer could sense if a user was having trouble with
an application and intuitively offer advice. The irritating
paperclip that embodies Microsoft's Office Assistant could be a
thing of the past. The software industry has tried to make
applications more intelligent but many fall far short of being
genuinely useful. However, this could be about to change.
Kate Hone, a lecturer in the department of information systems and
computing at Brunel University, is the principal investigator in a
project that aims to evaluate the potential for emotion-recognition
technology to improve the quality of human-computer interaction.
Her study is part of a larger area of computer science called
affective computing, which examines how computers affect and can
influence human emotion. Hone described her research at Brunel as a
human factor investigation. She said, "We are trying to build a
system that recognises emotion to support human-computer
recognition."
The project, called Eric (Emotional Recognition for Interaction
with Computers) has three main goals. First, Hone is looking at the
extent to which people will naturally express emotions when they
know they are interacting with an emotion-detecting computer.
Second, she wants to identify the conditions under which emotion
detection can lead to improvements in system usability. And third,
the research aims to provide "human factors" guidelines on the
deployment of emotion recognition technology that can help the
developers of such systems to meet the needs of real users.
"If you take facial expressions, which are a universal means of
communication, you can use algorithms to detect if the face is
looking unhappy," Hone said. By recognising facial expressions,
Hone said Eric could be used in applications ranging from home
entertainment to education.
For instance, she said in e-learning, the computer could detect how
puzzled a pupil was. Potentially, the computer would be able to
deal with user frustration by offering help when appropriate. The
technology could be applied to computer games, interactive horror
movies (are you scared enough?), or on a website, where the level
of usability could be gauged.
Computers equipped with a video camera can be used to capture the
image of a human face. One of the problems the researchers at
Brunel need to overcome is how to map facial muscles. According to
Hone, a technique known as Facial Action Coding System is one of
the most highly developed methods for coding facial expression. It
is based on the analysis of small facial movements, which are
visible to human observers and discriminable from each other.
"Many of the approaches used in speech recognition can be applied
to recognising emotion through facial recognition," Hone said. For
example, both are described as "natural" modes of communication,
with the implication that what is natural in the human-human
context should also improve human interactions with
computers.
Both technologies also face similar challenges. For instance, just
as the characteristics of speech vary from person to person, so do
the characteristics of emotional expression. This means systems
must either be trained to work for individual users (as in
speaker-dependent speech recognition) or attempt to work for all
users (speaker- or user-independent).
Similarly, while speech recognition faces the problem of detecting
discrete words within the continuous stream of speech, emotion
recognition technology will face the problem of detecting discrete
emotional states within a constantly varying input signal. Early
speech recognisers were "isolated-word" recognisers and relied upon
users deliberately pausing between utterances.
During the summer, Brunel University will be running a simulation
designed to evaluate how people respond to computers that exhibit
emotional recognition. Hone said that while it is possible to
perform facial recognition when the subject is not moving, speed of
processing is not yet fast enough for real-time recognition of
facial expressions.
What is affective computing?
Affective
computing can be defined as "computing that relates to, arises
from, or deliberately influences emotion". A number of different
types of research are encompassed within this term. For instance,
some artificial intelligence researchers in the field of affective
computing are interested in how emotion contributes to human and,
by analogy, computer problem solving or decision making; others are
concerned with enabling human-human communication of emotion
through the medium of computer networks. Underlying many of these
different strands of research is work on understanding the nature
of emotion and how it should be represented.
http://affect.media.mit.edu
CV: Kate Hone
Kate Hone is a lecturer in the department of IS and computing at
Brunel University. She has previously been a lecturer in the school
of computer science and IT at the University of Nottingham. Her PhD
was on the human factors of speech recognition systems. She also
holds degrees in experimental psychology and work design and
ergonomics. She has previously received EPSRC Fast Stream funding
for an 11-month project investigating user interactions with speech
recognition systems. She is currently supervising two PhD students
and is involved in the Millennium Homes project.
http://www.brunel.ac.uk/~csstksh/
eric.htm