ISCA Archive Interspeech 2014
ISCA Archive Interspeech 2014

Modeling therapist empathy through prosody in drug addiction counseling

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

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.

doi: 10.21437/Interspeech.2014-55

Cite as: Xiao, B., Bone, D., Segbroeck, M.V., Imel, Z.E., Atkins, D.C., Georgiou, P.G., Narayanan, S.S. (2014) Modeling therapist empathy through prosody in drug addiction counseling. Proc. Interspeech 2014, 213-217, doi: 10.21437/Interspeech.2014-55

  author={Bo Xiao and Daniel Bone and Maarten Van Segbroeck and Zac E. Imel and David C. Atkins and Panayiotis G. Georgiou and Shrikanth S. Narayanan},
  title={{Modeling therapist empathy through prosody in drug addiction counseling}},
  booktitle={Proc. Interspeech 2014},