inf5460 - Applied AI - Multimodal-Multisensor Interfaces III: Language Processing, Software, Commercialization, and Emerging Directions (Complete module description)

Module label	Applied AI - Multimodal-Multisensor Interfaces III: Language Processing, Software, Commercialization, and Emerging Directions
Module code	inf5460
Credit points	3.0 KP
Workload	90 h
Institute directory	Department of Computing Science
Applicability of the module	Master's Programme Computing Science (Master) > Angewandte Informatik
Responsible persons	Sonntag, Daniel (module responsibility) Lehrenden, Die im Modul (authorised to take exams)
Prerequisites	basic concepts of Artificial Intelligence, Human-Computer Interfaces
Skills to be acquired in this module	Learning methods of multimodal interaction, learning Human-Computer Interaction concepts. Professional competences The students work their way into the topic of multimodality (competence: basic concepts of multimodality, develop an intuition for multimodal approaches, multimodal fusion techniques Methological competences The students prepare a term paper on a special topic in the field of multimodality (competence: quick comprehension, structured literaturereview, precise expression). Social competences The students choose a topic and interact with each other and the supervising person (competence: communication skills, enthusiasm, initiative) Self competences The students work independently in a supervised setting (competencies: Personal responsibility, analytical thinking, organization, time management)
Module contents	This third seminar takes the contents of the first two seminars— namely, the motivations, foundational concepts, basic modality combinations, component analyses, and recognition and fusion techniques—to the next level. MMI 3 discusses how to design and build functioning multimodal-multisensor systems that can sustain real-world use. This seminar is most appropriate for graduate students and of primary interest to students studying computer science and information technology, human-computer interfaces, mobile and ubiquitous interfaces, affective and behavioral computing, machine learning, and related multidisciplinary majors. It is very useful if you want to work on practical applications, transfer of AI technology to application domains such as medicine and healthcare, and industrial prototypes. Afterward, students might engage in a hands-on project in which they design, build, and evaluate the performance of a multimodal system in our project group MMI II (https://elearning.uni- oldenburg.de/dispatch.php/course/details?sem_id=098bd500a63e7 23551364c7f921755b5&again=yes).
Recommended reading	The Handbook of Multimodal-Multisensor Interfaces: Language Processing, Software, Commercialization, and Emerging Directions - Volume 3" (https://dl.acm.org/doi/book/10.1145/3233795).
Links	https://uol.de/aai/lehre
Language of instruction	English
Duration (semesters)	1 Semester
Module frequency	every term
Module capacity	unlimited
Teaching/Learning method	S

Examination	Prüfungszeiten	Type of examination
Final exam of module	at the end of the lecture period	oral exam or portfolio or presentation

Type of course	Seminar
SWS	2
Frequency	SuSe and WiSe