Computer-Supported Interaction

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Computer-Supported Interaction

3 LP


#40181 / #4

Seit SS 2017

Fakultät IV

TEL 18

Institut für Softwaretechnik und Theoretische Informatik

34355300 FG S-Professur Quality and Usability

Möller, Sebastian

Hirsch, Tobias

Learning Outcomes

Students gain - Understanding of the most important principles of human-computer interaction. - Basic knowledge of multimodality and multimodal interacttion. - Basic knowledge of the gestural interaction. - Basic knowledge of speech production and perception. - Basic knowledge of speech recognition, acoustic feature extraction, and sequence modeling. - Basic knowledge of audio-visual and multimodal speech recognition. - Basic knowledge of machine learning and data mining. - Basic knowledge of machine translation and dialogue systems. - Presentation and knowledge transfer skills. Students will be able to - use the learned knowledge for designing exemplary human-computer interfaces


IV „Computer-supported Interaction“: This course gives an overview over statistical methods and their application on speech recognition, extraction of metadata (identity, age, gender, speech), audio-visual speech recognition, multi-lingual speech recognition, speech translation, multimodal interfaces: applications and technology (multimodal fusion und fission), Information Retrieval, Beamforming and microphon-arrays.

Module Components


All Courses are mandatory.

Course Name Type Number Cycle Language SWS
Computer-supported Interaction IV 0434 L 903 WS No information 2

Workload and Credit Points

Computer-supported Interaction (IV):

Workload description Multiplier Hours Total
Präsenzzeit 15.0 2.0h 30.0h
Vor-/Nachbereitung 15.0 4.0h 60.0h
90.0h (~3 LP)
The Workload of the module sums up to 90.0 Hours. Therefor the module contains 3 Credits.

Description of Teaching and Learning Methods

Lecture part: Lecture with practical presentations. Seminar part: Practical and theoretical presentations by students (optional).

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Basic knowledge of communications engineering and digital signal processing.

Mandatory requirements for the module test application:

No information

Module completion



Type of exam:

Written exam




90 min

Duration of the Module

This module can be completed in one semester.

Maximum Number of Participants

This module is limited to maximum capacity of 30.

Registration Procedures

Registration for the courses not necessary. Registratation for the exam through QISPOS or the examination office.

Recommended reading, Lecture notes

Lecture notes

Availability:  available

Electronical lecture notes

Availability:  available


Recommended literature
Bernd Pompino-Marschall: „Einführung in die Phonetik“ (de Gruyter, 1995)
Fred Jelinek: „Statistical methods for speech processing“ (MIT, 1997)
Keinosuke Fukunaga: „Statistical Pattern Recognition“ (Academic Press, 1990)
Laurence Rabiner and Biing-Hwang Juang: Fundamentals of speech recognition“ (Prentice Hall, 1993)
Richard O. Duda, Peter E. Hart, David G. Stork: „Pattern Classification“ (Wiley, 2000)
Tanja Schultz und Katrin Kirchhoff: "Multilingual Speech Processing" (Academic Press, 2006)
Thomas H. Cormen: „Introduction to Algorithms“ (MIT, 1990)

Assigned Degree Programs

This module is used in the following modulelists:

Students of other degrees can participate in this module without capacity testing.


The topics of the module can serve as a foundation of a bachelor or master thesis in the area. Es folgt eine Änderung der Prüfungsform von mündlich zu schriftlich im WS 2016/2017.