  In conversation-based psychotherapy, therapists use verbal techniques to help
clients express thoughts and feelings, and change behavior. In particular, how
well therapists convey empathy is an essential quality index of psychotherapy
sessions and is associated with psychotherapy outcome. In this paper, we
analyze the prosody of therapist speech and attempt to associate the
therapist's speaking style with subjectively perceived empathy. An automatic
speech and text processing system is developed to segment long recordings of
psychotherapy sessions into pause-delimited utterances with text
transcriptions. Data-driven clustering is applied to the utterances from
different therapists in multiple sessions. For each cluster, a typological
representation of utterance genre is derived based on quantized prosodic
feature parameters. Prominent speaking styles of the therapist can be observed
and interpreted from salient utterance genres that are correlated with empathy.
Using the salient utterance genres, an accuracy of $71\%$ is achieved in
classifying psychotherapy sessions into ``high" and ``low" empathy level.
Analysis of results suggests that empathy level tends to be (1) low if
therapists speak long utterances slowly or speak short utterances quickly; and
(2) high if therapists talk to clients with a steady tone and volume.
