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)
    • Artificial Neural Networks (ANNs)
    • 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



Please note that the lecture of the upcoming winter term will start on 02.11.2018. The first topic will be Noise Reduction.


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)
xx.xx.2019   F-SR II   xx:xx h        



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
xx.xx.2019   xx:xx h   xxx   Tobias Hübschen


Website News

01.10.2018: Dissertation of Philipp Bullding added.

14.08.2018: New section about our SONAR "sisters" added.

18.07.2018: New section about our Parkinson voice training game added.

07.07.2018: New lecture Fundamentals of Acoustics by Jan Abshagen added.

03.03.2018: Team wall added.

Recent Publications

E. Elzenheimer, H. Laufs, T. Sander-Thömmes, G. Schmidt: Magnetoneurograhy of an Electrically Stimulated Arm Nerve, Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials, Volume 63, Number 12, Pages 363-366, September 2018


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

DSS-Retreat 2018

At the end of October (24.10.2018 till 27.10.2018) we spent again a few days on the island Sylt to reflect our past, current, and future research work. This included all Ph.D. topics but also the general direction of our research. Of course, also teaching and team related issues were discussed. Beside all that official work we also enjoyed the time on that beautiful island with several common ...

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