“You’re as Sick as You Sound”: Using Computational Approaches for Modeling Speaker State to Gauge Illness and Recovery

Abstract

Recently, researchers in computer science and engineering have begun to explore the possibility of finding speech-based correlates of various medical conditions using automatic, computational methods. If such language cues can be identified and quantified automatically, this information can be used to support diagnosis and treatment of medical conditions in clinical settings and to further fundamental research in understanding cognition. This chapter reviews computational approaches that explore communicative patterns of patients who suffer from medical conditions such as depression, autism spectrum disorders, schizophrenia, and cancer. There are two main approaches discussed: research that explores features extracted from the acoustic signal and research that focuses on lexical and semantic features. We also present some applied research that uses computational methods to develop assistive technologies. In the final sections we discuss issues related to and the future of this emerging field of research. Keywords IntroductionMany medical conditions (e.g., depression, autism spectrum disorders (ASD), schizophrenia, as well as cancer) affect the communication patterns of the individuals who suffer from them. Researchers in psychology and psycho-linguistics have a long tradition of studying the speech and language of patients who suffer from these conditions to identify cues, with the hope of leveraging these cues for both

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