Lecture "Pattern Recognition"

Basic Information

Lecturers:   Gerhard Schmidt (lecture) and Tobias Hübschen (exercise)
Room:   F-SR-II
Language:   English
Target group:   Students in electrical engineering and computer engineering
Prerequisites:   Basics in system theory

In this lecture the basics of speech, audio, and music signal processing are treated. Often schemes that are based on statistical optimization are utilized for these applications. The involved cost function are matched to the human audio perception.

Topic overview:

  • Preprocessing to reduce signal distortions
    • Noise reduction
    • Beamforming
  • Speech and speaker recognition
    • Fundamentals of speech generation
    • Feature extraction
    • Gaussian mixture models (GMMs)
    • Hidden Markov models (HMMs)
    • Recognition of speech and speakers
  • Enhancement of signal playback
    • Extending the bandwidth of speech signals
    • Equalization of loudspeakers
    • Upmix of stereo signals for playback with more than two loudspeakers



It is now possible to reserve your examination time slot via our booking system. Please note that the exams on 28.03.2018 have been canceled. Please make sure to book a slot for your exam.


Lecture Slides

The slides of the lecture can be found here.


Matlab Demos

  Matlab demo (GUI based) for adaptive noise suppression
  Matlab demo (GUI based) for linear prediction



Please note that the questionnaires will be uploaded every week before the excercises, if you download them earlier, you won't get the most recent version.

de en    
  Questionnaire for the lecture "Noise Suppression"
  Questionnaire for the lecture "Beamforming"
  Questionnaire for the lecture "Feature extraction"
  Questionnaire for the lecture "Codebook training"
  Questionnaire for the lecture "Bandwidth extension"
  Questionnaire for the lecture "Gaussian Mixture Models"
  Questionnaire for the lecture "Speaker recognition"
  Questionnaire for the lecture "Hidden Markov Models"
  Questionnaire for the lecture "Speech recognition"



At the end of the semester, each student will give a talk about a certain topic. The aim is both to give you the chance to work on a pattern recognition-related topic that interests you, and to improve your presentational skills. The talk is also a prerequisite for your admission to the exam. The talks should be held in English and should take ten minutes, plus 2.5 minutes of discussion and 2.5 minutes of feedback. Please write an email to This email address is being protected from spambots. You need JavaScript enabled to view it. to reserve your topic.

Below you can find the schedule of the talks.

Date   Room   Time   Topic   Presenter(s)
19.01.2018   F-SR-II   10:00 h   Beamforming using Artificial Neural Networks   Nico Simoski
19.01.2018   F-SR-II   10:15 h   Genetic Algorithms   Bastian Kaulen
19.01.2018   F-SR-II   10:30 h   Adaptive Filters   Tim Benedikt Kupke
02.02.2018   F-SR-II   08:20 h   Speaker Recognition using Neural Networks   Patricia Piepjohn
02.02.2018   F-SR II   08:35 h   Proper Orthogonal Decomposition based Cancer Detection Technique   Sunasheer Bhattacharjee
02.02.2018   F-SR II   08:50 h   Decision Tree   Ali Hadidi
02.02.2018   F-SR II   09:05 h   Image Feature Detection   Karl Heger
02.02.2018   F-SR II   09:30 h   Pattern Recognition for Earthquake Detection   Jonas Weiss
02.02.2018   F-SR II   09:45 h   Fuzzy Logic in Pattern Recognition   Malte Wrobel
02.02.2018   F-SR II   10:00 h   Optimization Criteria for Noise Suppression
  Christian Olsiewski
02.02.2018   F-SR II   10:15 h   Pattern Recognition based Kalman Filter for Indoor Localization using TDOA algorithm   Simon Helling, Fabian Heuer
09.02.2018   F-SR II   08:20 h   Face Recognition using Neural Networks   Anton Lösch
09.02.2018   F-SR II   08:35 h   Noise-Adaptive Hidden Markov Models based on Wiener Filters   Avitha Francis
09.02.2018   F-SR II   08:50 h   Handwriting Recognition   Torben Krause
09.02.2018   F-SR II   09:15 h   Google Deep Dream   Egzon Miftaraj, Gerrit Oldenburger
09.02.2018   F-SR II   09:45 h   Speech Emotion Recognition   Hamed Tavakol



Below is the list of students with their exam dates. If you do not have a date for the exam yet please use the oral exam booking system on this website. You can find the booking system here.

Date   Time   Students (matriculation numbers)   Assessor
19.02.2018   08:00 h   1008366, 1018201   Tobias Hübschen
19.02.2018   10:00 h   1019245, 1003235   Tobias Hübschen
19.02.2018   11:00 h   1122961   Tobias Hübschen
19.02.2018   14:00 h   1018092, 1018127   Tobias Hübschen
19.02.2018   15:00 h   1113778   Tobias Hübschen
12.03.2018   10:00 h   1112513, 1017831, 1012485   Tobias Hübschen
26.03.2018   13:30 h   1016014   Tobias Hübschen
29.03.2018   16:00 h   1117882   Tobias Hübschen
29.03.2018   16:30 h   1018104   Tobias Hübschen
29.03.2018   17:00 h   6023   Tobias Hübschen
29.03.2018   17:30 h   1015888   Tobias Hübschen


Website News

03.03.2018: Team wall added.

28.02.2018: News wall added.

20.01.2017: Talk from Dr. Sander-Thömmes added.

12.01.2018: New RED section on Trend Removal added.

29.12.2017: Section Years in Review added.

Recent Publications

T. O. Wisch, T. Kaak, A. Namenas, G. Schmidt: Spracherkennung in stark gestörten Unterwasserumgebungen, Proc. DAGA 2018

S. Graf, T. Herbig, M. Buck, G. Schmidt: Low-Complexity Pitch Estimation Based on Phase Differences Between Low-Resolution Spectra, Proc. Interspeech, pp. 2316 -2320, 2017


Prof. Dr.-Ing. Gerhard Schmidt

E-Mail: gus@tf.uni-kiel.de

Christian-Albrechts-Universität zu Kiel
Faculty of Engineering
Institute for Electrical Engineering and Information Engineering
Digital Signal Processing and System Theory

Kaiserstr. 2
24143 Kiel, Germany

Recent News

New PhDs in the DSS Team

Since January this year we have two new PhD students in the team: Elke Warmerdam and Finn Spitz.

Elke is from Amsterdam and she works in the neurology department in the university hospital in the group of Prof. Maetzler. Her research topic is movement analysis of patients with neurologic disorders. Elke cooperates with us in signal processing related aspects of her research. Elke plays ...

Read more ...