16th Annual Conference of the International Speech Communication Association

Dresden, Germany
September 6-10, 2015

Predicting Therapist Empathy in Motivational Interviews Using Language Features Inspired by Psycholinguistic Norms

James Gibson (1), Nikolaos Malandrakis (1), Francisco Romero (1), David C. Atkins (2), Shrikanth S. Narayanan (1)

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

Therapist language plays a critical role in influencing the overall quality of psychotherapy. Notably, it is a major contributor to the perceived level of empathy expressed by therapists, a primary measure for judging their efficacy. We explore psycholinguistics inspired features for predicting therapist empathy. These features model language which conveys information about affective and cognitive processes, which is central to the therapist expressing understanding of the patient's perspective. We describe the dimensional features obtained based on psycholinguisitic norms, and their application to predicting empathy expressed in motivational interviewing sessions for addiction counseling. We compare these to standard lexical features (n-grams) and demonstrate that these features contain complementary information for predicting therapist empathy. The highest empathy prediction results achieved are 75.28% UAR and 0.6112 Spearman's correlation.

Full Paper

Bibliographic reference.  Gibson, James / Malandrakis, Nikolaos / Romero, Francisco / Atkins, David C. / Narayanan, Shrikanth S. (2015): "Predicting therapist empathy in motivational interviews using language features inspired by psycholinguistic norms", In INTERSPEECH-2015, 1947-1951.