Biosignal-adaptive Cognitive Systems

In my talk, I will describe technical cognitive systems that automatically adapt to users’ needs by interpreting their biosignals. Human behavior includes physical, mental, and social actions that emit a range of biosignals which can be captured by a variety of sensors. The processing and interpretation of such biosignals provides an inside perspective on human physical and mental activities, complementing the traditional approach of merely observing human behavior. As great strides have been made in recent years in integrating sensor technologies into ubiquitous devices and in machine learning methods for processing and learning from data, I argue that the time has come to harness the full spectrum of biosignals to understand user needs. I will present illustrative cases ranging from silent and imagined speech interfaces that convert myographic and neural signals directly into audible speech, to interpretation of human attention and decision making from multimodal biosignals.

Tanja Schultz

Prof. Dr.-Ing. Tanja Schultz received the diploma and doctoral degrees in Informatics from University of Karlsruhe and a Master degree in Mathematics and Sport Sciences from Heidelberg University, both in Germany. Since 2015 she is Professor for Cognitive Systems of the Faculty of Mathematics & Computer Science at the University of Bremen, Germany. Prior to Bremen she spent 7 years as Professor for Cognitive Systems at KIT (2007-2015) and over 20 years as Researcher (2000-2007) and adjunct Research Professor (2007-2022) at the Language Technologies Institute at Carnegie Mellon, PA USA. In 2007, she founded the Cognitive Systems Lab (CSL) where she and her team combine machine learning methods with innovations in biosignal processing to create technologies such as “Silent Speech Interfaces” and “Brain-to-Speech”.

Professor Schultz is a recognized scholar in the field of multilingual speech recognition and cognitive technical systems, is a Fellow of the IEEE, elected in 2020 “for contributions to multilingual speech recognition and biosignal processing”; a Fellow of the International Speech Communication Association, elected in 2016 “for contributions to multilingual speech recognition and biosignal processing for human-machine interaction”; a Fellow of the European Academy of Science and Arts (2017), and a Fellow of the Asian-Pacific Artificial Intelligence Association (2021). She is the spokesperson of the University Bremen high-profile area “Minds, Media, Machines” and the DFG Research Unit “Lifespan AI: From longitudinal data to lifespan inference in health”. She serves on the board of directors for the DFG CRC 1320 EASE, the DFG RTG 2739 KD2School – Designing Adaptive Systems for Economic Decision Making, and the Leibniz ScienceCampus on Digital Public Health.