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Expressive Conversational-Behavior Generation Models for Advanced Interaction within Multimodal User Interfaces (Hardcover)
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Expressive Conversational-Behavior Generation Models for Advanced Interaction within Multimodal User Interfaces (Hardcover)
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The aim of the book is to represent a flexible and efficient
algorithm and a novel system used for the planning, generation, and
realisation of conversational behavior (co-verbal behavior). Such
behavior is best described as a set of moving body parts, which are
meaningful. In terms of prosody, it is synchronised with the
accompanying speech. The movement and shapes generated as a
co-verbal behavior represent a contextual link between a repertoire
of independent motor skills (shapes, movements, and poses that
conversational agent can reproduce and execute), and the
intent/meaning of spoken sequences (context). The actual
intent/meaning of spoken content is identified through
language-dependent linguistic markers and prosody. The knowledge
databases used to determine the intent/meaning of text are based on
the linguistic analysis and classification of the text into
semiotic classes and subclasses achieved through annotation of
multimodal corpora based on the proposed EVA annotation scheme. The
scheme allows for capturing features at a functional
(context-dependent), as well as at a descriptive
(context-independent) level. The functional level captures
high-level features that describe the correlation between speech
and co-verbal behavior, whereas the descriptive level allows us to
capture and define body-poses and shapes independently of verbal
content and in high-resolution. The annotation scheme, therefore,
not only interlinks speech and gesture at a semiotic level, but
also serves as a basis for the creation of a context independent
repertoire of movement and shapes. The process of generating the
co-verbal behavior is, in this book, divided into two phases. The
first phase deals with the classification of intent and its
synchronisation with the verbal content and prosody. The second
phase then transforms the planned and synchronised behavior into a
co-verbal animation performed by an embodied conversational agent
(ECA). In order to be able to extrapolate intent from arbitrary
text-sequences, the algorithm for the formulation of behavior
deduces meaning/intent in regard to the semiotic intent.
Furthermore, the algorithm considers the linguistic features of
arbitrary and un-annotated text and select primitive gestures based
on semiotic nuclei, as identified by semiotic classification and
further modeled by the predicted prosodic features of speech to be
generated by a general text-to-speech system (TTS). The output of
the phase for formulation of behavior is represented as a
hierarchical procedure encoded in XML format, and as a speech
sequence generated by TTS. The procedural description is
event-oriented and represents a well-defined structure of
consecutive movements of body-parts, as well as of body-parts
moving in parallel. The second phase of the novel architecture
transforms the procedural descriptions into a series of coherent
animations of individual parts of the articulated embodied
conversational agent. In this regard a novel ECA-based realisation
framework named EVA-framework is also represented. It supports a
real-time realisation of procedural animation descriptions and
plans on multi-part mesh-based models, by using skeletal animation,
blend shape animation, and the animation of predefined
(pre-recorded) animated segments. This book, therefore, considers a
complete design and implementation of an expressive model for the
generation of co-verbal behavior, which is able to transform
un-annotated text into a speech-synchronised series of animated
sequences.
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