phy696 - Advanced Topics Speech and Audio Processing (Complete module description)

phy696 - Advanced Topics Speech and Audio Processing (Complete module description)

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Module label Advanced Topics Speech and Audio Processing
Modulkürzel phy696
Credit points 6.0 KP
Workload 180 h
(
Attendance: 56 hrs, Self study: 124 hrs
)
Institute directory Institute of Physics
Verwendbarkeit des Moduls
  • Master's Programme Engineering Physics (Master) > Schwerpunkt: Acoustics
Zuständige Personen
  • Doclo, Simon (module responsibility)
  • Doclo, Simon (Prüfungsberechtigt)
  • Gerkmann, Timo (Prüfungsberechtigt)
Prerequisites
Basic principles of signal processing (preferably successfully completed the course Signal- und Systemtheorie and/or Blockpraktikum Digitale Signalverarbeitung)
Skills to be acquired in this module
The students will gain in-depth knowledge on the subjects' speech and audio processing. The practical part of the course mediates insight about important properties of the methods treated in a self-study approach, while the application and transfer of theoretical concepts to practical applications is gained by implementing algorithms on a computer.
Module contents
After reviewing the basic principles of speech processing and statistical signal processing (adaptive filtering, estimation theory), this course covers techniques and underlying algorithms that are essential in many modern-day speech communication and audio processing systems (e.g. mobile phones, hearing aids, headphones): acoustic echo and feedback cancellation, noise reduction, dereverberation, microphone and loudspeaker array processing, active noise control. During the exercises a typical hands-free speech communication or audio processing system is implemented (in Matlab).
Literaturempfehlungen
J. Benesty, M. M. Sondhi, Y. Huang: Handbook of Speech Processing, Springer, 2008.;
P. Vary, R. Martin: Digital Speech Transmission, Wiley, 2006.;
P. Loizou: Speech Enhancement: Theory and Practice, CRC Press, 2007.;
S. Vaseghi: Advanced Digital Signal Processing and Noise Reduction, Wiley, 2006.;
S. Haykin: Adaptive Filter Theory, Prentice Hall, 2013.
Links
Language of instruction English
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Type of module Wahlpflicht / Elective
Module level MM (Mastermodul / Master module)
Teaching/Learning method Lecture: 2hrs/week, Exercise: 2hrs/week
Previous knowledge Basic principles of discrete-time signal processing (preferably completed the course Digital Signal Processing). In addition, Matlab programming skills are required
Examination Prüfungszeiten Type of examination
Final exam of module
Exam or presentation or oral exam or homework or practical report
Form of instruction Lecture
SWS 4
Frequency SoSe oder WiSe
Workload Präsenzzeit 56 h