Linguistic Signal

Linguistic signal research focuses on understanding how language encodes meaning and influences communication, encompassing both subtle cues and overt expressions. Current research employs machine learning models, including transformer-based architectures and variational autoencoders, to analyze various linguistic features, from micro-level elements like backchannels to higher-level aspects like dialogue structure and semantic underspecification. This work aims to improve language technologies, such as dialogue systems and text simplification tools, by better understanding how linguistic signals relate to meaning, bias, and effective human-computer interaction, ultimately leading to more robust and equitable AI systems.