Lecture "Pattern Recognition and Machine Learning"
| Basic Information | |
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| Lecturers: | Gerhard Schmidt (lecture) and Tobias Hübschen, Bastian Kaulen (exercise) |
| Room: | online until further notice |
| Language: | English |
| Target group: | Students in electrical engineering and computer engineering |
| Prerequisites: | Basics in system theory |
| Contents: |
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:
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News
Due to the current rising Covid-19 numbers, lecture and exercise will be held online starting Nov. 23.
A preliminary lecture and exercise schedule for WS 21/21 is now available.
The lecture will be given in seminar room F/SR-I and can be attended according to the university's current rules. Until further notice, the lecture will, additionally, be live streamed via zoom. The link will be provided through the corresponding Olat course.
There are two student talk sessions, one in December and one in January. For the first session please sign up no later than 09.12.2021. For the second session please sign up until 16.01.22. Giving the talk is a requirement to sit the exam. More information can be found below.
Remember to register for the exam in the QiS system. Without such a registration we will have to cancel any exam slot you booked with us. Booking of exam slots is possible here.
Schedule
The following schedule regarding lectures and excercises is preliminary and may be adapted during the semester. The lecture will usually take place from 14:00 h - 16:30 h.
| Date | Lecture | Exercise |
|---|---|---|
| 26.10.2021 | Introduction | - |
| 02.11.2021 | Noise Suppression + Beamforming | Noise Suppression (video) |
| 09.11.2021 | Beamforming + Feature Extractiom | Beamforming (video) |
| 16.11.2021 | Feature Extraction + Codebook Training | Feature Extraction (video) |
| 23.11.2021 | Codebook Training + Bandwidth Extension | Codebook Training (video) |
| 30.11.2021 | Bandwidth Extension | Bandwidth Extension (video) + Question time with content per request (start time will be communicated) |
| 07.12.2021 | Gaussian Mixture Models | Gaussian Mixture Models (video) |
| 14.12.2021 | Student Talks | Student talks |
| 11.01.2022 | Neural Networks | Neural Networks (video) |
| 18.01.2022 | Hidden Markov Models | Hidden Markov Models (video) |
| 25.01.2022 | Student Talks | Student talks |
| 01.02.2022 | Speaker and Speech Recognition | Question time + content per request (start time will be approx. 16:00 h), Speaker and Speech Recognition (video) |
Lecture Slides
| Link | Content |
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Slides of the lecture "Introduction" (Introduction, boundary conditions of the lecture, applications) |
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Slides of the lecture "Noise Suppression" (Noise suppression, dereverberation, speech reconstruction) |
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Slides of the lecture "Beamforming" (Fixed and adaptive beamforming, postfiltering) |
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Slides of the lecture "Feature Extraction" (Linear prediction, cepstrum, mel-filtered cepstral coefficients) |
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Slides of the lecture "Codebook Training" (K-means algorithm, LBG algorithms) |
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Slides of the lecture "Bandwidth Extension" (Model-bases approaches, evaluation) |
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Slides of the lecture "Gaussian Mixture Models (GMMs)" (Training with the EM algorithm, applications) |
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Slides of the lecture "Neural networks" (Network types, training procecures) |
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Slides of the lecture "Hidden Markov Models (HMMs)" (Efficient probability calculation, training of HMMs) |
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Slides of the lecture "Speaker and Speech Recognition" (Application of GMMs and HMMs, speech dialog systems) |
Matlab Demos
| Link | Content |
|---|---|
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Matlab demo (GUI based) for adaptive noise suppression |
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Matlab demo (GUI based) for linear prediction |
Exercises
For each lecture topic an on-demand video will be provided. On 30.11.2021 and on 01.02.2022 there will be an in-presence exercise to discuss your questions and requested topics. You may send in questions (if you want the answer to be supported by slides) or exercise topic suggestions to This email address is being protected from spambots. You need JavaScript enabled to view it. at any time. Both exercise sessions can be viewed using the lecture's zoom link.
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Noise suppression:
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Beamforming:
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Feature extraction:
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Codebook training:
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Bandwidth extension:
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Gaussian Mixture Models:
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Neural Networks:
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Hidden Markov Models:
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Speaker and Speech Recognition:
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Talks
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. For the first and the second talk session, the talk registration deadlines are 09.12.2021 and 16.01.2022, respectively.
Below you can find the preliminary schedule of the talks.
| Date | Room | Time | Topic | Presenter(s) |
|---|---|---|---|---|
| 14.12.2021 | zoom | 14:05 h | A Scalable Framework for Multiple Speaker Localization and Tracking | Arthur Lepsien |
| 14.12.2021 | zoom | 14:20 h | Interpretability Methods for Deep Neural Networks in Medical Image Analysis | Moritz Boueke |
| 14.12.2021 | zoom | 14:35 h | Data Mining in Healthcare Applications | Golam Sarowar Jahan Rifat |
| 14.12.2021 | zoom | 14:50 h | Generative Adverserial Networks | Henrik Horst |
| 14.12.2021 | zoom | 15:05 h | Face Recognition Based on Deep Learning | Karoline Gussow |
| 14.12.2021 | zoom | 15:20 h | break | |
| 25.01.2022 | zoom | 14:05 h | Support Vector Machines | Tim Johannisson |
| 25.01.2022 | zoom | 14:20 h | Decision Tree and Random Forest | Piotr Smietana |
| 25.01.2022 | zoom | 14:35 h | Feedforward Neural Networks | Abidur Rahman |
| 25.01.2022 | zoom | 14:50 h | Speaker Localization using Beamforming | Klara Görnig |
| 25.01.2022 | zoom | 15:05 h | Character Recognition using Machine Learning | Patricia Fuchs |
| 25.01.2022 | zoom | 15:20 h | break | |
| 25.01.2022 | zoom | 15:30 h | k-Nearest-Neighbor Simulator for Weather Variables | Simon Hesselbrock |
| 25.01.2022 | zoom | 15:45 h | Music Chord Recognition based on Neural Networks | Jan-Niklas Busse |
| 25.01.2022 | zoom | 16:05 h | Deep Learning for Video Game Playing | Marco Driesen |
| 25.01.2022 | zoom | 16:20 h | Gesture Recognition using Hidden Markov Models | Konstantinos Karatziotis |
| 25.01.2022 | zoom | 16:35 h | Cryptocurrencies Price Prediction using Machine Learning | Mohammadmahdi Asrar |
| 25.01.2022 | zoom | 16:50 h | break | |
| 25.01.2022 | zoom | 17:00 h | Edge Detection: Signal Processing vs. Neural Networks | Finn Bathel |
| 25.01.2022 | zoom | 17:15 h | Machine Learning based Failure Management in Optical Communications | Leon Neidhardt |
| 25.01.2022 | zoom | 17:30 h | Signature Recognition using Machine Learning | Wajid Ali |
| 25.01.2022 | zoom | 17:45 h | Singing Voice Separation from Monaural Recordings | Nico Töppe |
| 25.01.2022 | zoom | 18:00 h | Neural Networks for Speaker Separation | Finn Röhrdanz |
| 25.01.2022 | zoom | 18:15 h | Next-Generation Machine Learning for Biological Networks | Torben Niklas Lundt |
| Evaluation | |||
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Current evaluation | |
Completed evaluations |
A new podcast on our research on signal processing for underwater applications is online now. Liv Schnoor (previously Presser) interviewed Karoline Gussow, Bastian Kaulen, Gerhard Schmidt, and Owe Wisch on our latest research. It was really fun for us and the time (about on hour) was over really soon.