topical media & game development
research directions -- embodied conversational agents
A variety of applications may benefit from deploying
embodied conversational agents, either in the form
of animated humanoid avatars or, more simply, as a 'talking head'.
An interesting example is provided by
Signing Avatar,
a system that allows for translating arbitrary text in both spoken
language and sign language for the deaf, presented by animated
humanoid avatars.
Here the use of animated avatars is essential to communicate
with a particular group of users, using the sign language
for the deaf.
Other applications of embodied conversational agents
include e-commerce and social marketing,
although in these cases it may not always be evident that
animated avatars or faces actually do provide added value.
Another usage of embodied conversational agents
may be observed in virtual environments
such as Active Worlds,
blaxxun Community
and Adobe Atmosphere.
Despite the rich literary background of such environments,
including Neil Stephenson's Snow Crash,
the functionality of such agents is usually rather shallow,
due to the poor repertoire of gestures and movements
on the one hand and the restricted computational model
underlying these agents on the other hand.
In effect, the definition of agent avatars in virtual
environments generally relies on a proprietary
scripting language which, as in the case
of blaxxun Agents, offers only limited
pattern matching and a fixed repertoire of built-in actions.
In contrast, the scripting language for Signing Avatar
is based on the H-Anim standard
and allows
for a precise definition of a complex repertoire
of gestures, as exemplified by the sign language for the deaf.
Nevertheless, also this scripting language is of a
proprietary nature and does not allow for higher-order
abstractions of semantically meaningful behavior.
scripting behavior
In this section we introduced a software platform for agants.
This platform not only offers
powerful computational capabilities
but also an expressive
scripting language (STEP) for defining gestures and driving the behavior
of our humanoid agent avatars.
The design of the scripting language was motivated by
the requirements listed below.
STEP
- convenience -- for non-professional authors
- compositional semantics -- combining operations
- re-definability -- for high-level specification of actions
- parametrization -- for the adaptation of actions
- interaction -- with a (virtual) environment
Our scripting language STEP
meets these requirements.
STEP is based on dynamic logic [DL] and allows
for arbitrary abstractions using the primitives and
composition operators provided by our logic.
STEP is implemented on top of DLP,
As a last bit of propaganda:
DLP+X3D
The DLP+X3D platform provides together with the STEP
scripting language
the computational facilities for defining semantically meaningful
behaviors and allows for a rich presentational
environment,
in particular 3D virtual environments that may include
streaming video, text and speech.
See appendix D for more details.
evaluation criteria
The primary criterium against which to evaluate
applications that involve embodied conversational
agents is whether the application becomes more effective
by using such agents. Effective, in terms of communication
with the user.
Evidently, for the Signing Avatar application this
seems to be quite obvious.
For other applications, for example negotiation in e-commerce,
this question might be more difficult to answer.
As concerns the embedding of conversationl agents in VR,
we might make a distinction between presentational VR,
instructional VR and educational VR.
An example of educational VR is described in [EducationalVR].
No mention of agents was made in the latter reference though.
In instructional VR, explaining for example the use of a machine,
the appearance of a conversational agent seems to be quite natural.
In presentational VR, however,
the appearance of such agents might be considered as no more
than a gimmick.
Considering the use of agents in applications in general,
we must make a distinction between information agents,
presentation agents and conversational agents.
Although the boundaries between these categories are not clearcut,
there seems to be an increasing degree of interactivity with the user.
From a system perspective, we might be interested in what range of
agent categories the system covers.
Does it provide support for managing information and possibly
information retrieval?
Another issue in this regard could be whether the system
is built around open standards, such as XML and X3D, to allow for
the incorporation of a variety of content.
Last but not least, from a user perspective, what seems
to matter most is the naturalness of the (conversational) agents.
This is determined by the graphical quality, as well as
contextual parameters, that is how well the agent is embedded
in its environment.
More important even are emotive parameters,
that is the mood and style (in gestures and possibly speech)
with which the agents manifest themselves.
In other words, the properties that determine whether
an agent is (really) convincing.
(C) Æliens
04/09/2009
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