At the Institute of Human-Machine Communication we develop novel technologies and concepts for intuitive human interaction with all types of computers and computer-controlled systems. We research and develop cutting-edge methods of machine intelligence combined with modern techniques of signal processing and pattern recognition. One of our major objectives is to explore innovations for Virtual Reality (VR) and Augmented Reality (AR), both of which are closely linked to ongoing research in user interfaces, data visualization and automotive user design. In this regard, constructing adequate multimodal interfaces is a vital requirement in order to facilitate effortless participation in today’s computing infrastructure. Another area of our research deals with person identification by their biometric features such as face or gait. The high diversity of input data requires elaborate methods for feature extraction and pattern recognition to be engineered.

Professorship for Audio Information Processing (AIP)

Prof. Dr.-Ing. Bernhard Seeber

We investigate the information processing in the human auditory system and use this knowledge to improve hearing devices and audio systems.

Our research focusses on signal coding for neuronal protheses (cochlear implants), on the analysis of acoustic scenes and on modern techniques for sound reproduction via multiple loudspeakers.

International Year of Sound 2020

Group Visual Efficient Sensing for the Perception-Action Loop (VESPA) (2014 - 2019)

Dr.-Ing. Michael Dorr

The interdisciplinary International Junior Research Group "Visual Efficient Sensing for the Perception-Action Loop" will address fundamental problems in basic and clinical vision science and will build more efficient computer vision systems.

The junior research group will develop improved computer vision algorithms. The models and systems developed by the junior research group can automatically identify critical information without limitations. Interactive devices will be developed that continuously monitor the user's eye movements and modify in real time the scene contents in order to guide the user to attend the critical locations.

Associated Group: Machine Intelligence & Signal Processing (MISP)

Priv.-Doz. Dr.-Ing. habil. Björn W. Schuller
(von Oktober 2014 bis 2017 an der Universität Passau
seit Oktober 2017 an der Universität Augsburg)

Our research focuses on the development and evaluation of innovative methods in the field of Machine Intelligence together with modern Signal Processing algorithms.

Application domains in the context of Human-Machine Communication and Media Retrieval include intelligent processing of speech and language, music, video, and physiological data.