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Purpose Conversational entrainment, the phenomenon whereby communication partners synchronize their behavior, is considered essential for productive and fulfilling conversation. Lack of entrainment could, therefore, negatively impact conversational success. Although studied in many disciplines, entrainment has received limited attention in the field of speech-language pathology, where its implications may have direct clinical relevance. Method A novel computational methodology, informed by expert clinical assessment of conversation, was developed to investigate conversational entrainment across multiple speech dimensions in a corpus of experimentally elicited conversations involving healthy participants. The predictive relationship between the methodology output and an objective measure of conversational success, communicative efficiency, was then examined. Results Using a real versus sham validation procedure, we find evidence of sustained entrainment in rhythmic, articulatory, and phonatory dimensions of speech. We further validate the methodology, showing that models built on speech signal entrainment measures consistently outperform models built on nonentrained speech signal measures in predicting communicative efficiency of the conversations. Conclusions A multidimensional, clinically meaningful methodology for capturing conversational entrainment, validated in healthy populations, has implications for disciplines such as speech-language pathology where conversational entrainment represents a critical knowledge gap in the field, as well as a potential target for remediation.

Syncing Up for a Good Conversation: A Clinically Meaningful Methodology for Capturing Conversational Entrainment in the Speech Domain