Signal Processing for Audio Technology
Module number: EI7493
Duration: 1 semester
Occurence: Summer semester
Number of ECTS: 8
Professor in charge: Bernhard Seeber
Amount of work
Study hours: 90
Self-studying hours: 990
Description of achievement and assessment methods
The different learning outcomes are examined in separate, targeted ways.
Knowledge based learning outcomes are tested in a 20-minute oral exam.
The ability to individually solve problems as well as general and practical skills are continuously examined as appropriate for a practical course. Students receive ≥5 programming assignments from which they have to complete 5 assignments. Individual progress is monitored during the practical course and the final, submitted computer code to each assignment is graded. Individual supervision is offered during the times of the practical course.
The final grade is composed of the following exam elements:
- 50% oral exam
- 50% programming assignments
Exam type: written and oral
Exam duration: 20min.
Possibility of re-taking: In the next semester: No At the end of the semester: No
Written paper: No
Lecture Audio Communication (BSc)
Lecture Psychoacoustics and Audiological Applications advised
Programming skills in Matlab are helpful
The module consists of a lecture and a practical part. The following topics are part of the lecture:
AD-DA conversion (sampling), z-transformation, rate conversion, DFT
Fundamentals of real-time processing: blockwise convolution with DFT (overlap-add/overlap-save)
Filtering of audio signals: IIR and FIR filters, equalizers (high pass, low pass, band pass and shelving filters), auditory filters (BARK filterbank, Gammatone)
Inverse filtering for spectral equalization
Dynamic range adjustment: compression and limiting, attack and release time constants, distortions, multiband compression
Music effects: Echo, chorus and phase effects (flanger, phaser), distortion, gateing, wah-wah, tube amplifier
Vocoders for speech and music (Time stretching, pitch shifting, whisperization)
Directional microphones: Beamformer
Binaural technology: measurement and application of head-related transfer functions and room impulse responses for auralization
Simulation of room reverberation
In the practical part students will solve programming assignments which cover basic methods for audio signal processing in a practical context. The topics will be selected from the lecture, for example implementations of real time filtering, music effects, dynamic compressors, or binaural synthesis. Besides methods for audio processing the module will teach programming skills in Matlab.
After participating in this module students will be able to understand and practically apply basic techniques for audio signal processing. The module will also train programming skills using Matlab.
Teaching and learning methods
Lecture and self-study of the lecture content;
Programming assignments with supervision and self-study of additional material.
Lecture with projected notes, printed material and explanations on practical examples;
Programming assignments in the practical course are supervised in small groups by a tutor.
Oppenheim, A. V., and Schafer, R. W. (2009) Discrete-time signal processing, Prentice-Hall International, Englewood Cliffs, NJ
Zölzer (2008) Digital Audio Signal Processing, John Wiley & Sons.
Porat (1996) A Course in Digital Signal Processing, John Wiley & Sons.