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20.01.2022 02:33:27
phy677 - Speech processing (Complete module description)
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Module label Speech processing
Module code phy677
Credit points 6.0 KP
Workload 180 h
180 h (Präsenzzeit 56h, Selbststudium: 124h)
Institute directory Institute of Physics
Applicability of the module
  • Master's Programme Engineering Physics (Master) > Schwerpunkt: Acoustics
Responsible persons
Doclo, Simon (Authorized examiners)
Kollmeier, Birger (Authorized examiners)
Meyer, Bernd (Authorized examiners)
Doclo, Simon (Module responsibility)
Skills to be acquired in this module
The students will be able to (a) explain the foundations of speech production, perception and analysis, (b) understand the mathematical and information-theoretical principles of speech signal processing, and (c) apply the studied methods to explain the working principle of practical speech processing systems.
Module contents
Speech production and perception, speech analysis, speech signal processing (STFT, LPC, cepstrum, speech enhancement), speech coding, speech synthesis, automatic speech recognition, speech quality and intelligibility measures, selected topics on speech processing research.
Reader's advisory

M. R. Schroeder, Computer Speech: Recognition, Compression, Synthesis, Springer, 2013.

J. R. Deller, J. H. L. Hansen, J. G. Proakis: Discrete-Time Processing of Speech Signals, Wiley-IEEE Press, 1999.

P. Vary, R. Martin: Digital Speech Transmission, Wiley, 2006.

J. Benesty, M. M. Sondhi, Y. Huang: Handbook of Speech Processing, Springer, 2008.

D. Yu, L. Deng: Automatic Speech Recognition: A Deep Learning Approach, Springer, 2015.
Language of instruction English
Duration (semesters) 1 Semester
Module frequency jährlich
Module capacity unlimited
Modullevel / module level MM (Mastermodul / Master module)
Modulart / typ of module Wahlpflicht / Elective
Lehr-/Lernform / Teaching/Learning method Vorlesung: 2 SWS, Übung: 2 SWS
Vorkenntnisse / Previous knowledge Introductory signals and systems lecture
Examination Time of examination Type of examination
Final exam of module
Course type Lecture
Frequency SoSe oder WiSe
Workload attendance 56 h