|Lecturers:||Gerhard Schmidt (lecture) and Tobias Hübschen (exercise)|
|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.
Starting this winter semester, the exercise will be extended by practical tasks such as training a neural network using Python and TensorFlow. For this practical part of the excercise you are recommended to bring your own laptop. The exercise will be conducted as blocks, the schedule can be found below.
Exam appointments have to be acquired offline this semester. The following dates are available:
- 10.02.2020 (morning + afternoon)
- 19.02.2020 (morning) -> fully booked
- 27.03.2020 (morning) -> fully booked
Appointments are available in room D-016. You may sit the exam individually or in groups of two.
The following schedule regarding lectures and excercises is preliminary and may be adapted during the semester. Each date refers to the time slot from 13:00 h until 16:30 h.
|29.10.2019||Noise Suppression + Beamforming (part 1)|
|05.11.2019||Beamforming (part 2) + exercise|
|12.11.2019||Feature Extraction + Codebooks (part 1)|
|19.11.2019||Codebooks (part 2) + Bandwidth Extension|
|03.12.2019||Gaussian Mixture Models + Neural Networks (part 1)|
|10.12.2019||Neural Networks (part 2) + exercise|
|07.01.2020||Hidden Markov Models|
|14.01.2020||Speaker and Speech Recognition + exercise|
|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.
Below you can find the schedule of the talks.
|28.01.2020||F-SR I||13:05 h||Random Forests||Bastian Schroeter|
|28.01.2020||F-SR I||13:20 h||Transfer Learning||Kristina Apelt|
|28.01.2020||F-SR I||13:35 h||Reinforcement Learning||Daniaal Dar|
|28.01.2020||F-SR I||13:50 h||Transformer Models||Sönke Bartels|
|28.01.2020||F-SR I||14:05 h||Face Recognition||Yasin Akbaba|
|28.01.2020||F-SR I||14:30 h||Biological Pattern Recognition||Jannek Winter|
|28.01.2020||F-SR I||14:45 h||Self Learning||Tim Schmidt|
|28.01.2020||F-SR I||15:00 h||Vehicular Crash Detection using Hidden Markov Models||Toni Lekic|
Programs and Data
|Current evaluation||Completed evaluations|