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phenomenon, and participants do not alternate their roles like in a
volley match, just uttering sentences while speaking and freezing
while listening. Communication is much more like a dance, in which
people move together, sometime they lead and sometime they follow,
waltzing toward a common goal: exchange information, coordinate
actions, display emotional state, establish a relationship and fulfill
their needs (Castelfranchi and Parisi, 1980; Poggi, 2007). So, like the
speaker, listeners play an important role in the conversation, and
they have to actively participate in the interaction in order to push it
forward and make the speaker go on. In fact, whenever people listen
to somebody, they do not assimilate passively all her/his words, but
they actively participate in the interaction providing information about
how they feel and what they think of the speaker's speech. Listeners
emit expressions like “a-ah”, “mmh” or “yes” to assure
grounding
1
,
nod their head in agreement, smile to show liking, frown if they do
not understand and shake their head to make clear that they refuse
the speaker's words. In short, while listening, people assume an active
role in the interaction showing above all that they are attending the
exchange of communication. According to the listener's behavior, the
speaker can estimate how her/his interlocutor is reacting and can
decide how to carry on the interaction: for example, by interrupting the
conversation if the listener is not interested or rephrasing a sentence
if the listener showed signs of incomprehension.
Due to the undeniable importance of the behavior showed by
listeners, ECAs must be able to generate this type of behavior in
order to interact successfully with a user. To pursue such a goal, the
listener's behavior must be investigated thoroughly as well as the
signals performed by interlocutors. This chapter aims to provide such
a proper survey, reporting also the progress made by researchers in
the human-machine interface field to create ECAs able to show an
appropriate listening behavior. The chapter is structured in three parts.
In the first one, we investigate the behavior shown by listeners during
an interaction. The second part is devoted to studies that use virtual
agents to determine listener signals. Finally, in the third part, we focus
on virtual agent systems able to generate the listener behavior while
the agent interacts with a user.
2. Listener Behavior
Many studies have been conducted on the behavioral signals displayed
by the listener during conversations in order to understand and define
1
Grounding: the process by which partners in a dialogue gain common ground, that
is mutual belief and shared conception (Clark and Schaefer, 1989).
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