15th Annual Conference of the International Speech Communication Association

September 14-18, 2014

Modeling Therapist Empathy Through Prosody in Drug Addiction Counseling

Bo Xiao (1), Daniel Bone (1), Maarten Van Segbroeck (1), Zac E. Imel (2), David C. Atkins (3), Panayiotis G. Georgiou (1), Shrikanth S. Narayanan (1)

(1) University of Southern California, USA
(2) University of Utah, USA
(3) University of Washington, USA

Empathy measures the capacity of the therapist to experience the same cognitive and emotional dispositions as the patient, and is a key quality factor in counseling. In this work we build computational models to infer the empathy of therapist using prosodic cues. We extract pitch, energy, jitter, shimmer and utterance duration from the speech signal, and normalize and quantize these features in order to estimate the distribution of certain prosodic patterns during each interaction. We find significant correlation between empathy and the distribution of prosodic patterns, and achieve 75% accuracy in classifying therapist empathy levels using this distribution. Experiment results suggest high pitch and energy of the therapist are negatively correlated with empathy. These observations agree with domain literature and human intuition.

Full Paper

Bibliographic reference.  Xiao, Bo / Bone, Daniel / Segbroeck, Maarten Van / Imel, Zac E. / Atkins, David C. / Georgiou, Panayiotis G. / Narayanan, Shrikanth S. (2014): "Modeling therapist empathy through prosody in drug addiction counseling", In INTERSPEECH-2014, 213-217.