Abstract

Empathy involves understanding other people’s situation, perspective, and feelings. In clinical interactions, it helps clinicians establish rapport with a patient and support patient-centered care and decision making. Understanding physician communication through observation of audio-recorded encounters is largely carried out with manual annotation and analysis. However, manual annotation has a prohibitively high cost. In this paper, a multimodal system is proposed for the first time to automatically detect empathic interactions in recordings of real-world face-to-face oncology encounters that might accelerate manual processes. An automatic speech and language processing pipeline is employed to segment and diarize the audio as well as for transcription of speech into text. Lexical and acoustic features are derived to help detect both empathic opportunities offered by the patient, and the expressed empathy by …

Date

2020

Authors

Zhuohao Chen, James Gibson, Ming-Chang Chiu, Qiaohong Hu, Tara K Knight, Daniella Meeker, James A Tulsky, Kathryn I Pollak, Shrikanth Narayanan

Conference

2020 IEEE International Conference on Healthcare Informatics (ICHI)

Pages

1-8

Publisher

IEEE