Keynote Speech 5: Wednesday 09:00-10:00, December 20th, 2023

Abstract

Neural Signal Interpretation for Spoken Communication

This talk presents advancements in decoding neural signals, providing further insights into the intricacies of spoken communication. Delving into both speech production and speech perception, we discuss low latency processing of neural signals from surface EEG, stereotactic EEG, and intracranial EEG using machine learning methods. Practical implications and human-centered applications are considered, including silent speech interfaces, neuro-speech prostheses, and the detection of auditory attention and distraction in communication. This presentation aims to spark curiosity about the evolving landscape of neural signal interpretation and its impact on the future of spoken communication.

Biography

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 Communication" 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 Communi¬ca¬tion 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 elected 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.