Linguistic Entrainment

Linguistic entrainment describes the tendency for conversational partners to unconsciously synchronize their linguistic patterns, including vocabulary, syntax, and even prosody. Current research focuses on quantifying this alignment using deep neural networks, such as BERT and transformer-based models, to analyze both semantic and auditory features in dialogues, exploring the relationship between these aspects of entrainment and its role in successful human-human and human-machine interaction. Understanding this phenomenon has implications for improving the naturalness and effectiveness of conversational agents and offers insights into social interaction dynamics, including the diagnosis of conditions like autism spectrum disorder.