  We address the problem of designing a conversational avatar capable of a
sequence of casual conversations with older adults. Users at risk of
loneliness, social anxiety or a sense of ennui may benefit from practicing such
conversations in private, at their convenience. We describe an automatic spoken
dialogue manager for LISSA, an on-screen virtual agent that can keep older
users involved in conversations over several sessions, each lasting 10-20
minutes. The idea behind LISSA is to improve users' communication skills by
providing feedback on their non-verbal behavior at certain points in the course
of the conversations. In this paper, we analyze the dialogues collected from
the first session between LISSA and each of 8 participants. We examine the
quality of the conversations by comparing the transcripts with those collected
in a WOZ setting. LISSA's contributions to the conversations were judged by
research assistants who rated the extent to which the contributions were
"natural", "on track", "encouraging", "understanding", "relevant", and
"polite". The results show that the automatic dialogue manager was able to
handle conversation with the users smoothly and naturally.
