Audio Processing Laboratory, Summer Term 2022
Objectives and Requirements
The objective of this lab course is to give students a hands on experience in audio processing. In particular, functions, transforms, and algorithms that are important for analyzing and processing audio signals are covered. The lab course is supervised by members of the AudioLabs team.
Requirements are a solid mathematical background, a good understanding of fundamentals in digital signal processing, as well as a general background and personal interest in audio.
Furthermore, experience with PYTHON and NUMPY is required. Experience with the R Programming language is beneficial (beginners tutorial is provided in the course material).
Registration via StudOn is required for this lab.
Registration is open from 28. Mar. 2022, 00:00 - 04. Apr 2022, 23:55.
For questions, please contact Yigitcan Özer.
The Audio Processing Laboratory will be offered as a fully virtual course this semester. As a consequence, all students who want to participate must have access to a computer capable of
- running the ZOOM video conferencing software, including audio and video transmission as well as screensharing.
- running a regular web browser to access our Python development environment.
The introductory meeting will take place on Friday, April 29th 2022, at 13:00 CEST via the ZOOM video conferencing tool. You MUST participate this meeting to be able to take the course, regardless of whether you are already admitted or on the waiting list. Students who do not attend the introductory meeting will be removed from the course. We will fill the free spots among those students from the waiting list who do attend the first meeting. Note that we can not guarantee a spot for all students on the waiting list. Links to the meeting will be provided via StudOn and mail.
The lab consists of one introduction session (2 hours) and five lab units.
Students will work on the lab units from home. Questions can be asked via mail and a StudOn forum. There will also be open question sessions on Mondays 11:15 - 12:15 in the weeks of the lab exams. Some homework exercises are to be done in written form on paper. These must be submitted on Tuesdays, 12pm via StudOn (as scans or photographs). Students will then be examined in pairs via video conferencing, including screen sharing. All solutions must be ready for the examination. These examinations will take place on Thursdays 12:00 - 16:40 and Fridays 10:00 - 14:00. Students will be assigned a slot among these times.
The schedule of the five lab units will be
Lab 1: Short-Time Fourier Transform and Chroma Features
Supervisors: Yigitcan Özer, Sebastian Rosenzweig
Question session: 16.05.2022, 11:15 - 12:15
Homework submission: 17.05.2022, 12pm
- 19.05.2022: 12:00 - 16:40
- 20.05.2022: 10:00 - 14:00
Lab 2: Convolution and Correlation for Real-time Audio Processing
Supervisors: Lorenz Schmidt, Niklas Winter
Question session: 30.05.2022, 11:15 - 12:15
Homework submission: 31.05.2022, 12pm
- 02.06.2022: 12:00 - 16:40
- 03.06.2022: 10:00 - 14:00
Lab 3: Speech Analysis
Supervisors: Martin Strauß, Richard Füg
Question session: 20.06.2022, 11:15 - 12:15
Homework submission: 21.06.2022, 12pm
- 23.06.2022: 12:00 - 16:40
- 24.06.2022: 10:00 - 14:00
Lab 4: Statistical Methods for Audio Experiments
Supervisors: Pablo Delgado, Martin Müller
Question session: 04.07.2022, 11:15 - 12:15
Homework submission: 05.07.2022, 12pm
- 07.07.2022: 12:00 - 16:40
- 08.07.2022: 10:00 - 14:00
Lab 5: Speech Enhancement Using Microphone Arrays
Supervisors: Carlotta Anemüller, Julian Wechsler
Question session: 18.07.2022, 11:15 - 12:15
Homework submission: 19.07.2022, 12pm
- 21.07.2022: 12:00 - 16:40
- 22.07.2022: 10:00 - 14:00
- Attendance is mandatory for all meetings and test sessions.
- CME students are required to have passed the CME Prep-Course in order to participate in this lab.
- Link to notebook server (logins will be distributed in the introductory meeting)
- An introduction to Python and Jupyter Notebooks: Link
- Python docs: Link
- Jupyter Notebook docs: Link, Try yourself: Link
- An introduction to SciPy: Link
- The lab courses are designed to be worked on in groups of 2-3 participants
- Individual points for each of the groups participants will be assigned by the supervisors (Points: 0=no pass, 1=minimal pass , 2=pass, 3=excellent).
To pass the lab course you need to pass all five individual labs by having at least 1 point in all five labs. Altogether at least 7 points.